Overview

Dataset statistics

Number of variables62
Number of observations88
Missing cells2160
Missing cells (%)39.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.8 KiB
Average record size in memory497.5 B

Variable types

Numeric12
Categorical41
Unsupported9

Alerts

airdate has constant value "2020-12-09" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 88 distinct values High cardinality
name has a high cardinality: 82 distinct values High cardinality
_links.self.href has a high cardinality: 88 distinct values High cardinality
_embedded.show.url has a high cardinality: 67 distinct values High cardinality
_embedded.show.name has a high cardinality: 66 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 59 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 57 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 64 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 64 distinct values High cardinality
_embedded.show.summary has a high cardinality: 55 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 67 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 67 distinct values High cardinality
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
number is highly correlated with rating.average and 3 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 8 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.rating.average and 5 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with number and 1 other fieldsHigh correlation
number is highly correlated with season and 5 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.id is highly correlated with number and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with number and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.rating.average and 4 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 2 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.rating.average and 4 other fieldsHigh correlation
id is highly correlated with url and 27 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 41 other fieldsHigh correlation
season is highly correlated with url and 23 other fieldsHigh correlation
number is highly correlated with url and 36 other fieldsHigh correlation
type is highly correlated with url and 26 other fieldsHigh correlation
airtime is highly correlated with id and 40 other fieldsHigh correlation
airstamp is highly correlated with id and 42 other fieldsHigh correlation
runtime is highly correlated with url and 38 other fieldsHigh correlation
summary is highly correlated with id and 40 other fieldsHigh correlation
image.medium is highly correlated with id and 39 other fieldsHigh correlation
image.original is highly correlated with id and 39 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with url and 42 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 43 other fieldsHigh correlation
_embedded.show.language is highly correlated with url and 42 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 40 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 23 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with url and 40 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.updated is highly correlated with url and 26 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 37 other fieldsHigh correlation
number has 4 (4.5%) missing values Missing
runtime has 4 (4.5%) missing values Missing
summary has 69 (78.4%) missing values Missing
rating.average has 86 (97.7%) missing values Missing
image.medium has 64 (72.7%) missing values Missing
image.original has 64 (72.7%) missing values Missing
_embedded.show.language has 2 (2.3%) missing values Missing
_embedded.show.runtime has 23 (26.1%) missing values Missing
_embedded.show.averageRuntime has 3 (3.4%) missing values Missing
_embedded.show.ended has 50 (56.8%) missing values Missing
_embedded.show.officialSite has 13 (14.8%) missing values Missing
_embedded.show.rating.average has 82 (93.2%) missing values Missing
_embedded.show.network has 88 (100.0%) missing values Missing
_embedded.show.webChannel.id has 6 (6.8%) missing values Missing
_embedded.show.webChannel.name has 6 (6.8%) missing values Missing
_embedded.show.webChannel.country has 88 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 37 (42.0%) missing values Missing
_embedded.show.dvdCountry has 88 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 86 (97.7%) missing values Missing
_embedded.show.externals.thetvdb has 35 (39.8%) missing values Missing
_embedded.show.externals.imdb has 49 (55.7%) missing values Missing
_embedded.show.image.medium has 3 (3.4%) missing values Missing
_embedded.show.image.original has 3 (3.4%) missing values Missing
_embedded.show.summary has 12 (13.6%) missing values Missing
image has 88 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 43 (48.9%) missing values Missing
_embedded.show.webChannel.country.code has 43 (48.9%) missing values Missing
_embedded.show.webChannel.country.timezone has 43 (48.9%) missing values Missing
_embedded.show._links.nextepisode.href has 81 (92.0%) missing values Missing
_embedded.show.network.id has 75 (85.2%) missing values Missing
_embedded.show.network.name has 75 (85.2%) missing values Missing
_embedded.show.network.country.name has 75 (85.2%) missing values Missing
_embedded.show.network.country.code has 75 (85.2%) missing values Missing
_embedded.show.network.country.timezone has 75 (85.2%) missing values Missing
_embedded.show.network.officialSite has 88 (100.0%) missing values Missing
_embedded.show.webChannel has 88 (100.0%) missing values Missing
_embedded.show.image has 88 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 86 (97.7%) missing values Missing
_embedded.show.dvdCountry.code has 86 (97.7%) missing values Missing
_embedded.show.dvdCountry.timezone has 86 (97.7%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.url is uniformly distributed Uniform
_embedded.show.name is uniformly distributed Uniform
_embedded.show.officialSite is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show.image.medium is uniformly distributed Uniform
_embedded.show.image.original is uniformly distributed Uniform
_embedded.show.summary is uniformly distributed Uniform
_embedded.show._links.self.href is uniformly distributed Uniform
_embedded.show._links.previousepisode.href is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:39:51.678506
Analysis finished2022-09-06 02:40:08.402691
Duration16.72 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2027522.557
Minimum1941971
Maximum2386105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:08.478206image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1941971
5-th percentile1966970.25
Q11978051.5
median1985463.5
Q32044222.25
95-th percentile2194435.85
Maximum2386105
Range444134
Interquartile range (IQR)66170.75

Descriptive statistics

Standard deviation85209.44614
Coefficient of variation (CV)0.04202638627
Kurtosis4.01542291
Mean2027522.557
Median Absolute Deviation (MAD)11846.5
Skewness2.000435218
Sum178421985
Variance7260649711
MonotonicityNot monotonic
2022-09-05T21:40:08.595377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21796121
 
1.1%
19868711
 
1.1%
19854641
 
1.1%
19854631
 
1.1%
19849491
 
1.1%
19849481
 
1.1%
19776391
 
1.1%
19776381
 
1.1%
19761941
 
1.1%
19761931
 
1.1%
Other values (78)78
88.6%
ValueCountFrequency (%)
19419711
1.1%
19451451
1.1%
19588661
1.1%
19600331
1.1%
19644941
1.1%
19715691
1.1%
19719501
1.1%
19726431
1.1%
19726441
1.1%
19726451
1.1%
ValueCountFrequency (%)
23861051
1.1%
23181011
1.1%
22059711
1.1%
22059701
1.1%
21954121
1.1%
21926231
1.1%
21820811
1.1%
21796121
1.1%
21748991
1.1%
21661941
1.1%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size832.0 B
https://www.tvmaze.com/episodes/2179612/kontakty-1x29-kontakty-v-telefone-nikolaa-soboleva-klava-koka-eldar-dzarahov-andrej-malahov-edvard-bil
 
1
https://www.tvmaze.com/episodes/1986871/kotiki-1x08-seria-8
 
1
https://www.tvmaze.com/episodes/1985464/you-complete-me-1x08-episode-8
 
1
https://www.tvmaze.com/episodes/1985463/you-complete-me-1x07-episode-7
 
1
https://www.tvmaze.com/episodes/1984949/dream-detective-1x10-episode-10
 
1
Other values (83)
83 

Length

Max length149
Median length98
Mean length81.04545455
Min length57

Characters and Unicode

Total characters7132
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2179612/kontakty-1x29-kontakty-v-telefone-nikolaa-soboleva-klava-koka-eldar-dzarahov-andrej-malahov-edvard-bil
2nd rowhttps://www.tvmaze.com/episodes/1986871/kotiki-1x08-seria-8
3rd rowhttps://www.tvmaze.com/episodes/1983257/mertvye-dusi-1x01-seria-1
4th rowhttps://www.tvmaze.com/episodes/1983258/mertvye-dusi-1x02-seria-2
5th rowhttps://www.tvmaze.com/episodes/1971569/mermaid-prince-2x09-episode-9

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179612/kontakty-1x29-kontakty-v-telefone-nikolaa-soboleva-klava-koka-eldar-dzarahov-andrej-malahov-edvard-bil1
 
1.1%
https://www.tvmaze.com/episodes/1986871/kotiki-1x08-seria-81
 
1.1%
https://www.tvmaze.com/episodes/1985464/you-complete-me-1x08-episode-81
 
1.1%
https://www.tvmaze.com/episodes/1985463/you-complete-me-1x07-episode-71
 
1.1%
https://www.tvmaze.com/episodes/1984949/dream-detective-1x10-episode-101
 
1.1%
https://www.tvmaze.com/episodes/1984948/dream-detective-1x09-episode-91
 
1.1%
https://www.tvmaze.com/episodes/1977639/to-love-1x28-episode-281
 
1.1%
https://www.tvmaze.com/episodes/1977638/to-love-1x27-episode-271
 
1.1%
https://www.tvmaze.com/episodes/1976194/psych-hunter-1x28-episode-281
 
1.1%
https://www.tvmaze.com/episodes/1976193/psych-hunter-1x27-episode-271
 
1.1%
Other values (78)78
88.6%

Length

2022-09-05T21:40:08.706178image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179612/kontakty-1x29-kontakty-v-telefone-nikolaa-soboleva-klava-koka-eldar-dzarahov-andrej-malahov-edvard-bil1
 
1.1%
https://www.tvmaze.com/episodes/1986871/kotiki-1x08-seria-81
 
1.1%
https://www.tvmaze.com/episodes/1983257/mertvye-dusi-1x01-seria-11
 
1.1%
https://www.tvmaze.com/episodes/1983258/mertvye-dusi-1x02-seria-21
 
1.1%
https://www.tvmaze.com/episodes/1971569/mermaid-prince-2x09-episode-91
 
1.1%
https://www.tvmaze.com/episodes/1985044/wan-sheng-jie-2x11-enough-money-was-left-for-this-episode1
 
1.1%
https://www.tvmaze.com/episodes/2386105/xian-feng-jian-yu-lu-1x46-episode-461
 
1.1%
https://www.tvmaze.com/episodes/1985616/yi-nian-yong-heng-1x20-episode-201
 
1.1%
https://www.tvmaze.com/episodes/2096296/no-turning-back-romance-1x02-21
 
1.1%
https://www.tvmaze.com/episodes/2030019/dolls-frontline-2x11-episode-111
 
1.1%
Other values (78)78
88.6%

Most occurring characters

ValueCountFrequency (%)
e610
 
8.6%
-549
 
7.7%
s461
 
6.5%
/440
 
6.2%
t429
 
6.0%
o374
 
5.2%
a306
 
4.3%
w285
 
4.0%
i267
 
3.7%
p266
 
3.7%
Other values (30)3145
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4889
68.6%
Decimal Number990
 
13.9%
Other Punctuation704
 
9.9%
Dash Punctuation549
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e610
12.5%
s461
 
9.4%
t429
 
8.8%
o374
 
7.6%
a306
 
6.3%
w285
 
5.8%
i267
 
5.5%
p266
 
5.4%
m265
 
5.4%
d196
 
4.0%
Other values (16)1430
29.2%
Decimal Number
ValueCountFrequency (%)
1226
22.8%
2126
12.7%
0124
12.5%
9122
12.3%
371
 
7.2%
869
 
7.0%
466
 
6.7%
764
 
6.5%
661
 
6.2%
561
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/440
62.5%
.176
 
25.0%
:88
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4889
68.6%
Common2243
31.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e610
12.5%
s461
 
9.4%
t429
 
8.8%
o374
 
7.6%
a306
 
6.3%
w285
 
5.8%
i267
 
5.5%
p266
 
5.4%
m265
 
5.4%
d196
 
4.0%
Other values (16)1430
29.2%
Common
ValueCountFrequency (%)
-549
24.5%
/440
19.6%
1226
10.1%
.176
 
7.8%
2126
 
5.6%
0124
 
5.5%
9122
 
5.4%
:88
 
3.9%
371
 
3.2%
869
 
3.1%
Other values (4)252
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII7132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e610
 
8.6%
-549
 
7.7%
s461
 
6.5%
/440
 
6.2%
t429
 
6.0%
o374
 
5.2%
a306
 
4.3%
w285
 
4.0%
i267
 
3.7%
p266
 
3.7%
Other values (30)3145
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct82
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size832.0 B
Episode 9
 
3
Episode 10
 
2
Episode 28
 
2
Episode 8
 
2
Episode 27
 
2
Other values (77)
77 

Length

Max length93
Median length62
Mean length19.80681818
Min length1

Characters and Unicode

Total characters1743
Distinct characters128
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)87.5%

Sample

1st rowКОНТАКТЫ в телефоне Николая Соболева: Клава Кока, Эльдар Джарахов, Андрей Малахов, Эдвард Бил
2nd rowСерия 8
3rd rowСерия 1
4th rowСерия 2
5th rowEpisode 9

Common Values

ValueCountFrequency (%)
Episode 93
 
3.4%
Episode 102
 
2.3%
Episode 282
 
2.3%
Episode 82
 
2.3%
Episode 272
 
2.3%
КОНТАКТЫ в телефоне Николая Соболева: Клава Кока, Эльдар Джарахов, Андрей Малахов, Эдвард Бил1
 
1.1%
Episode 231
 
1.1%
Episode 191
 
1.1%
Episode 71
 
1.1%
Episode 181
 
1.1%
Other values (72)72
81.8%

Length

2022-09-05T21:40:08.817779image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode32
 
10.7%
10
 
3.3%
95
 
1.7%
the5
 
1.7%
24
 
1.3%
to4
 
1.3%
серия3
 
1.0%
vs3
 
1.0%
13
 
1.0%
83
 
1.0%
Other values (214)228
76.0%

Most occurring characters

ValueCountFrequency (%)
213
 
12.2%
e131
 
7.5%
o96
 
5.5%
i83
 
4.8%
a74
 
4.2%
s71
 
4.1%
r69
 
4.0%
n61
 
3.5%
t55
 
3.2%
d52
 
3.0%
Other values (118)838
48.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1159
66.5%
Uppercase Letter245
 
14.1%
Space Separator213
 
12.2%
Decimal Number80
 
4.6%
Other Punctuation35
 
2.0%
Dash Punctuation8
 
0.5%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%
Math Symbol1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e131
 
11.3%
o96
 
8.3%
i83
 
7.2%
a74
 
6.4%
s71
 
6.1%
r69
 
6.0%
n61
 
5.3%
t55
 
4.7%
d52
 
4.5%
p47
 
4.1%
Other values (49)420
36.2%
Uppercase Letter
ValueCountFrequency (%)
E38
 
15.5%
B13
 
5.3%
H13
 
5.3%
T13
 
5.3%
S12
 
4.9%
D10
 
4.1%
L10
 
4.1%
M9
 
3.7%
F9
 
3.7%
A9
 
3.7%
Other values (35)109
44.5%
Decimal Number
ValueCountFrequency (%)
217
21.2%
117
21.2%
010
12.5%
87
8.8%
96
 
7.5%
75
 
6.2%
45
 
6.2%
35
 
6.2%
54
 
5.0%
64
 
5.0%
Other Punctuation
ValueCountFrequency (%)
,11
31.4%
.7
20.0%
&5
14.3%
:4
 
11.4%
!3
 
8.6%
"2
 
5.7%
'1
 
2.9%
/1
 
2.9%
?1
 
2.9%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Math Symbol
ValueCountFrequency (%)
|1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1128
64.7%
Common339
 
19.4%
Cyrillic276
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e131
 
11.6%
o96
 
8.5%
i83
 
7.4%
a74
 
6.6%
s71
 
6.3%
r69
 
6.1%
n61
 
5.4%
t55
 
4.9%
d52
 
4.6%
p47
 
4.2%
Other values (42)389
34.5%
Cyrillic
ValueCountFrequency (%)
а25
 
9.1%
е24
 
8.7%
о16
 
5.8%
и15
 
5.4%
р14
 
5.1%
н13
 
4.7%
л12
 
4.3%
к11
 
4.0%
в9
 
3.3%
К8
 
2.9%
Other values (42)129
46.7%
Common
ValueCountFrequency (%)
213
62.8%
217
 
5.0%
117
 
5.0%
,11
 
3.2%
010
 
2.9%
-8
 
2.4%
.7
 
2.1%
87
 
2.1%
96
 
1.8%
75
 
1.5%
Other values (14)38
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1460
83.8%
Cyrillic276
 
15.8%
None7
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
 
14.6%
e131
 
9.0%
o96
 
6.6%
i83
 
5.7%
a74
 
5.1%
s71
 
4.9%
r69
 
4.7%
n61
 
4.2%
t55
 
3.8%
d52
 
3.6%
Other values (62)555
38.0%
Cyrillic
ValueCountFrequency (%)
а25
 
9.1%
е24
 
8.7%
о16
 
5.8%
и15
 
5.4%
р14
 
5.1%
н13
 
4.7%
л12
 
4.3%
к11
 
4.0%
в9
 
3.3%
К8
 
2.9%
Other values (42)129
46.7%
None
ValueCountFrequency (%)
í2
28.6%
á2
28.6%
ó2
28.6%
ø1
14.3%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct14
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.42045455
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:08.910505image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.25
95-th percentile26.45
Maximum2020
Range2019
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation422.6251218
Coefficient of variation (CV)4.475991181
Kurtosis18.12459218
Mean94.42045455
Median Absolute Deviation (MAD)0
Skewness4.4396774
Sum8309
Variance178611.9936
MonotonicityNot monotonic
2022-09-05T21:40:09.006087image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
154
61.4%
212
 
13.6%
20204
 
4.5%
44
 
4.5%
73
 
3.4%
32
 
2.3%
52
 
2.3%
101
 
1.1%
81
 
1.1%
61
 
1.1%
Other values (4)4
 
4.5%
ValueCountFrequency (%)
154
61.4%
212
 
13.6%
32
 
2.3%
44
 
4.5%
52
 
2.3%
61
 
1.1%
73
 
3.4%
81
 
1.1%
101
 
1.1%
111
 
1.1%
ValueCountFrequency (%)
20204
4.5%
311
 
1.1%
181
 
1.1%
141
 
1.1%
111
 
1.1%
101
 
1.1%
81
 
1.1%
73
3.4%
61
 
1.1%
52
2.3%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct42
Distinct (%)50.0%
Missing4
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean27.83333333
Minimum1
Maximum296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:09.112459image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.15
Q14.75
median11
Q328
95-th percentile95.3
Maximum296
Range295
Interquartile range (IQR)23.25

Descriptive statistics

Standard deviation49.51836299
Coefficient of variation (CV)1.779102862
Kurtosis19.65774899
Mean27.83333333
Median Absolute Deviation (MAD)8.5
Skewness4.144932508
Sum2338
Variance2452.068273
MonotonicityNot monotonic
2022-09-05T21:40:09.226920image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
28
 
9.1%
15
 
5.7%
35
 
5.7%
85
 
5.7%
94
 
4.5%
104
 
4.5%
73
 
3.4%
53
 
3.4%
183
 
3.4%
43
 
3.4%
Other values (32)41
46.6%
(Missing)4
 
4.5%
ValueCountFrequency (%)
15
5.7%
28
9.1%
35
5.7%
43
 
3.4%
53
 
3.4%
61
 
1.1%
73
 
3.4%
85
5.7%
94
4.5%
104
4.5%
ValueCountFrequency (%)
2961
1.1%
2951
1.1%
1481
1.1%
1101
1.1%
981
1.1%
801
1.1%
621
1.1%
611
1.1%
591
1.1%
561
1.1%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size832.0 B
regular
84 
significant_special
 
3
insignificant_special
 
1

Length

Max length21
Median length7
Mean length7.568181818
Min length7

Characters and Unicode

Total characters666
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular84
95.5%
significant_special3
 
3.4%
insignificant_special1
 
1.1%

Length

2022-09-05T21:40:09.330778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:09.428937image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular84
95.5%
significant_special3
 
3.4%
insignificant_special1
 
1.1%

Most occurring characters

ValueCountFrequency (%)
r168
25.2%
a92
13.8%
e88
13.2%
g88
13.2%
l88
13.2%
u84
12.6%
i17
 
2.6%
n9
 
1.4%
s8
 
1.2%
c8
 
1.2%
Other values (4)16
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter662
99.4%
Connector Punctuation4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r168
25.4%
a92
13.9%
e88
13.3%
g88
13.3%
l88
13.3%
u84
12.7%
i17
 
2.6%
n9
 
1.4%
s8
 
1.2%
c8
 
1.2%
Other values (3)12
 
1.8%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin662
99.4%
Common4
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r168
25.4%
a92
13.9%
e88
13.3%
g88
13.3%
l88
13.3%
u84
12.7%
i17
 
2.6%
n9
 
1.4%
s8
 
1.2%
c8
 
1.2%
Other values (3)12
 
1.8%
Common
ValueCountFrequency (%)
_4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r168
25.2%
a92
13.8%
e88
13.2%
g88
13.2%
l88
13.2%
u84
12.6%
i17
 
2.6%
n9
 
1.4%
s8
 
1.2%
c8
 
1.2%
Other values (4)16
 
2.4%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size832.0 B
2020-12-09
88 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters880
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-09
2nd row2020-12-09
3rd row2020-12-09
4th row2020-12-09
5th row2020-12-09

Common Values

ValueCountFrequency (%)
2020-12-0988
100.0%

Length

2022-09-05T21:40:09.504797image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:09.583818image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0988
100.0%

Most occurring characters

ValueCountFrequency (%)
2264
30.0%
0264
30.0%
-176
20.0%
188
 
10.0%
988
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number704
80.0%
Dash Punctuation176
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2264
37.5%
0264
37.5%
188
 
12.5%
988
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2264
30.0%
0264
30.0%
-176
20.0%
188
 
10.0%
988
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2264
30.0%
0264
30.0%
-176
20.0%
188
 
10.0%
988
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct14
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size832.0 B
47 
20:00
15 
06:00
10:00
 
4
19:30
 
4
Other values (9)
12 

Length

Max length5
Median length0
Mean length2.329545455
Min length0

Characters and Unicode

Total characters205
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)6.8%

Sample

1st row12:00
2nd row
3rd row
4th row
5th row11:00

Common Values

ValueCountFrequency (%)
47
53.4%
20:0015
 
17.0%
06:006
 
6.8%
10:004
 
4.5%
19:304
 
4.5%
12:002
 
2.3%
21:002
 
2.3%
00:002
 
2.3%
11:001
 
1.1%
05:001
 
1.1%
Other values (4)4
 
4.5%

Length

2022-09-05T21:40:09.665300image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0015
36.6%
06:006
 
14.6%
10:004
 
9.8%
19:304
 
9.8%
12:002
 
4.9%
21:002
 
4.9%
00:002
 
4.9%
11:001
 
2.4%
05:001
 
2.4%
17:351
 
2.4%
Other values (3)3
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0104
50.7%
:41
 
20.0%
222
 
10.7%
117
 
8.3%
66
 
2.9%
36
 
2.9%
95
 
2.4%
53
 
1.5%
71
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number164
80.0%
Other Punctuation41
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0104
63.4%
222
 
13.4%
117
 
10.4%
66
 
3.7%
36
 
3.7%
95
 
3.0%
53
 
1.8%
71
 
0.6%
Other Punctuation
ValueCountFrequency (%)
:41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common205
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0104
50.7%
:41
 
20.0%
222
 
10.7%
117
 
8.3%
66
 
2.9%
36
 
2.9%
95
 
2.4%
53
 
1.5%
71
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII205
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0104
50.7%
:41
 
20.0%
222
 
10.7%
117
 
8.3%
66
 
2.9%
36
 
2.9%
95
 
2.4%
53
 
1.5%
71
 
0.5%

airstamp
Categorical

HIGH CORRELATION

Distinct20
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size832.0 B
2020-12-09T12:00:00+00:00
42 
2020-12-09T05:00:00+00:00
2020-12-09T04:00:00+00:00
2020-12-09T11:00:00+00:00
2020-12-09T00:00:00+00:00
 
4
Other values (15)
26 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2200
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)10.2%

Sample

1st row2020-12-09T00:00:00+00:00
2nd row2020-12-09T00:00:00+00:00
3rd row2020-12-09T00:00:00+00:00
4th row2020-12-09T00:00:00+00:00
5th row2020-12-09T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-09T12:00:00+00:0042
47.7%
2020-12-09T05:00:00+00:006
 
6.8%
2020-12-09T04:00:00+00:005
 
5.7%
2020-12-09T11:00:00+00:005
 
5.7%
2020-12-09T00:00:00+00:004
 
4.5%
2020-12-09T19:30:00+00:004
 
4.5%
2020-12-09T02:00:00+00:004
 
4.5%
2020-12-09T17:00:00+00:003
 
3.4%
2020-12-09T15:00:00+00:002
 
2.3%
2020-12-09T13:00:00+00:002
 
2.3%
Other values (10)11
 
12.5%

Length

2022-09-05T21:40:09.749160image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-09t12:00:00+00:0042
47.7%
2020-12-09t05:00:00+00:006
 
6.8%
2020-12-09t04:00:00+00:005
 
5.7%
2020-12-09t11:00:00+00:005
 
5.7%
2020-12-09t00:00:00+00:004
 
4.5%
2020-12-09t19:30:00+00:004
 
4.5%
2020-12-09t02:00:00+00:004
 
4.5%
2020-12-09t17:00:00+00:003
 
3.4%
2020-12-09t13:00:00+00:002
 
2.3%
2020-12-09t10:00:00+00:002
 
2.3%
Other values (10)11
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0990
45.0%
2312
 
14.2%
:264
 
12.0%
-176
 
8.0%
1160
 
7.3%
990
 
4.1%
T88
 
4.0%
+88
 
4.0%
512
 
0.5%
39
 
0.4%
Other values (3)11
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1584
72.0%
Other Punctuation264
 
12.0%
Dash Punctuation176
 
8.0%
Uppercase Letter88
 
4.0%
Math Symbol88
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0990
62.5%
2312
 
19.7%
1160
 
10.1%
990
 
5.7%
512
 
0.8%
39
 
0.6%
46
 
0.4%
74
 
0.3%
81
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:264
100.0%
Dash Punctuation
ValueCountFrequency (%)
-176
100.0%
Uppercase Letter
ValueCountFrequency (%)
T88
100.0%
Math Symbol
ValueCountFrequency (%)
+88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2112
96.0%
Latin88
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0990
46.9%
2312
 
14.8%
:264
 
12.5%
-176
 
8.3%
1160
 
7.6%
990
 
4.3%
+88
 
4.2%
512
 
0.6%
39
 
0.4%
46
 
0.3%
Other values (2)5
 
0.2%
Latin
ValueCountFrequency (%)
T88
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0990
45.0%
2312
 
14.2%
:264
 
12.0%
-176
 
8.0%
1160
 
7.3%
990
 
4.1%
T88
 
4.0%
+88
 
4.0%
512
 
0.5%
39
 
0.4%
Other values (3)11
 
0.5%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)42.9%
Missing4
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean37.36904762
Minimum2
Maximum136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:09.832637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.3
Q119
median30.5
Q345
95-th percentile103.6
Maximum136
Range134
Interquartile range (IQR)26

Descriptive statistics

Standard deviation27.46028008
Coefficient of variation (CV)0.7348402443
Kurtosis3.352443052
Mean37.36904762
Median Absolute Deviation (MAD)14.5
Skewness1.643022805
Sum3139
Variance754.0669822
MonotonicityNot monotonic
2022-09-05T21:40:09.936039image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
4518
20.5%
309
 
10.2%
255
 
5.7%
604
 
4.5%
53
 
3.4%
333
 
3.4%
73
 
3.4%
123
 
3.4%
433
 
3.4%
1202
 
2.3%
Other values (26)31
35.2%
(Missing)4
 
4.5%
ValueCountFrequency (%)
21
 
1.1%
41
 
1.1%
53
3.4%
73
3.4%
82
2.3%
101
 
1.1%
123
3.4%
132
2.3%
152
2.3%
161
 
1.1%
ValueCountFrequency (%)
1361
 
1.1%
1211
 
1.1%
1202
2.3%
1061
 
1.1%
901
 
1.1%
721
 
1.1%
604
4.5%
581
 
1.1%
551
 
1.1%
531
 
1.1%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct19
Distinct (%)100.0%
Missing69
Missing (%)78.4%
Memory size832.0 B
<p>Go ahead. Ask her why she does it. Trixie and Katya spill the tea on power, power dynamics, and how to use your boobs to wield it over others,</p>
 
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<p>On the last leg of his journey across England, Robbie crosses an epic aqueduct near Stratford-upon-Avon and gets stuck in a lock in central Birmingham.</p>
 
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<p>Robbie navigates the mighty River Severn and takes an unexpected bath as he takes a tumble at the Tardebigge lock flight in Worcestershire.</p>
 
1
<p>Robbie gets stuck in the mud in Woodseaves Cutting and explores the charming canal-side village of Kinver in Staffordshire.</p>
 
1
Other values (14)
14 

Length

Max length514
Median length160
Mean length184.2631579
Min length61

Characters and Unicode

Total characters3501
Distinct characters72
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row<p>Go ahead. Ask her why she does it. Trixie and Katya spill the tea on power, power dynamics, and how to use your boobs to wield it over others,</p>
2nd row<p>The issue about Mariupol turned out to be one of the most difficult for Zhenya Sinelnikov, because many were waiting for it. At home, this city with a difficult fate will better show: a drama theater, a square, a city pier. Mariupol is the largest city on the Azov coast, the city is one of the industrial giants of Ukraine. Let's walk around Mariupol, as it was many years ago, and we will do it with the help of new - virtual technologies. And also remember the old heading - "Shopping at home is better."</p>
3rd row<p>A holiday gathering takes a strange turn when Ashley bumps her head and gets a glimpse of her near-distant future with Tío Victor, Tad, Stick and Brooke.</p>
4th row<p>Stuck on the couch with a broken leg, the Big Show watches as Cassy — aka Mrs. Claus — grants wild wishes while the girls scour the home for gifts.</p>
5th row<p>When Stolas hires I.M.P as bodyguards on a trip to Loo Loo Land, things sure do happen. <br /> </p>

Common Values

ValueCountFrequency (%)
<p>Go ahead. Ask her why she does it. Trixie and Katya spill the tea on power, power dynamics, and how to use your boobs to wield it over others,</p>1
 
1.1%
<p>Happy Holidays! BFFs Ruby Rose Turner (Coop &amp; Cami Ask the World), Ruth Righi (Sydney to the Max), and special guest Izabela Rose (Upside-Down Magic) compete to see who can make the best gingerbread house! </p>1
 
1.1%
<p>On the last leg of his journey across England, Robbie crosses an epic aqueduct near Stratford-upon-Avon and gets stuck in a lock in central Birmingham.</p>1
 
1.1%
<p>Robbie navigates the mighty River Severn and takes an unexpected bath as he takes a tumble at the Tardebigge lock flight in Worcestershire.</p>1
 
1.1%
<p>Robbie gets stuck in the mud in Woodseaves Cutting and explores the charming canal-side village of Kinver in Staffordshire.</p>1
 
1.1%
<p>Robbie battles his way through blanket weed on the Shropshire Union Canal and discovers industrial secrets in Audlem, Cheshire.</p>1
 
1.1%
<p>Hot Take breaks down the latest news about the Covid vaccine, the Georgia recount, and more with actor and activist Kal Penn. Plus, Tyler Templeton asks Uncle Squirrel to donate his organs to Rudy Giuliani. </p>1
 
1.1%
<p>Welcome to the SEASON 2 of our spooky and now FESTIVE show- Too Many Spirits! Join us as we read your submitted holiday ghost stories and enjoy cocktails prepared by freshman bartender, Steven Lim.</p>1
 
1.1%
<p>Arm takes viewers backstage of the MAMA OK photoshoot.</p>1
 
1.1%
<p>After falling in love with the heart, Dr. Devi Shetty takes the next step to become a cardiac surgeon. Then a visit with Mother Teresa changes his life.</p>1
 
1.1%
Other values (9)9
 
10.2%
(Missing)69
78.4%

Length

2022-09-05T21:40:10.035381image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the31
 
5.4%
and22
 
3.8%
to18
 
3.1%
a15
 
2.6%
in10
 
1.7%
of10
 
1.7%
with7
 
1.2%
his7
 
1.2%
p7
 
1.2%
as6
 
1.0%
Other values (360)443
76.9%

Most occurring characters

ValueCountFrequency (%)
550
15.7%
e297
 
8.5%
a224
 
6.4%
t212
 
6.1%
o202
 
5.8%
i186
 
5.3%
n172
 
4.9%
s171
 
4.9%
r160
 
4.6%
h129
 
3.7%
Other values (62)1198
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2550
72.8%
Space Separator559
 
16.0%
Uppercase Letter168
 
4.8%
Other Punctuation107
 
3.1%
Math Symbol96
 
2.7%
Dash Punctuation12
 
0.3%
Open Punctuation3
 
0.1%
Close Punctuation3
 
0.1%
Decimal Number3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e297
11.6%
a224
 
8.8%
t212
 
8.3%
o202
 
7.9%
i186
 
7.3%
n172
 
6.7%
s171
 
6.7%
r160
 
6.3%
h129
 
5.1%
p104
 
4.1%
Other values (18)693
27.2%
Uppercase Letter
ValueCountFrequency (%)
S22
13.1%
T18
 
10.7%
A17
 
10.1%
R15
 
8.9%
M12
 
7.1%
C10
 
6.0%
K7
 
4.2%
L6
 
3.6%
P6
 
3.6%
D6
 
3.6%
Other values (15)49
29.2%
Other Punctuation
ValueCountFrequency (%)
.36
33.6%
,35
32.7%
/26
24.3%
!3
 
2.8%
"2
 
1.9%
'2
 
1.9%
:1
 
0.9%
&1
 
0.9%
;1
 
0.9%
Space Separator
ValueCountFrequency (%)
550
98.4%
 9
 
1.6%
Math Symbol
ValueCountFrequency (%)
<48
50.0%
>48
50.0%
Dash Punctuation
ValueCountFrequency (%)
-10
83.3%
2
 
16.7%
Decimal Number
ValueCountFrequency (%)
22
66.7%
11
33.3%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2718
77.6%
Common783
 
22.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e297
 
10.9%
a224
 
8.2%
t212
 
7.8%
o202
 
7.4%
i186
 
6.8%
n172
 
6.3%
s171
 
6.3%
r160
 
5.9%
h129
 
4.7%
p104
 
3.8%
Other values (43)861
31.7%
Common
ValueCountFrequency (%)
550
70.2%
<48
 
6.1%
>48
 
6.1%
.36
 
4.6%
,35
 
4.5%
/26
 
3.3%
-10
 
1.3%
 9
 
1.1%
(3
 
0.4%
)3
 
0.4%
Other values (9)15
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3488
99.6%
None11
 
0.3%
Punctuation2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
550
15.8%
e297
 
8.5%
a224
 
6.4%
t212
 
6.1%
o202
 
5.8%
i186
 
5.3%
n172
 
4.9%
s171
 
4.9%
r160
 
4.6%
h129
 
3.7%
Other values (58)1185
34.0%
None
ValueCountFrequency (%)
 9
81.8%
ñ1
 
9.1%
í1
 
9.1%
Punctuation
ValueCountFrequency (%)
2
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing86
Missing (%)97.7%
Memory size832.0 B
10.0
8.0

Length

Max length4
Median length3.5
Mean length3.5
Min length3

Characters and Unicode

Total characters7
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row10.0
2nd row8.0

Common Values

ValueCountFrequency (%)
10.01
 
1.1%
8.01
 
1.1%
(Missing)86
97.7%

Length

2022-09-05T21:40:10.122524image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:10.207463image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
10.01
50.0%
8.01
50.0%

Most occurring characters

ValueCountFrequency (%)
03
42.9%
.2
28.6%
11
 
14.3%
81
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5
71.4%
Other Punctuation2
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
03
60.0%
11
 
20.0%
81
 
20.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
03
42.9%
.2
28.6%
11
 
14.3%
81
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
03
42.9%
.2
28.6%
11
 
14.3%
81
 
14.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct24
Distinct (%)100.0%
Missing64
Missing (%)72.7%
Memory size832.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/360/901422.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/720303.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/382/956556.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/286/716334.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/375/937751.jpg
 
1
Other values (19)
19 

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters1728
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901422.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719751.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719752.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726343.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726859.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/360/901422.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720303.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/382/956556.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716334.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/375/937751.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/311/778162.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719832.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719831.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719830.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719828.jpg1
 
1.1%
Other values (14)14
 
15.9%
(Missing)64
72.7%

Length

2022-09-05T21:40:10.277725image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/360/901422.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720303.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719751.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719752.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726343.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726859.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726860.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726861.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726862.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726863.jpg1
 
4.2%
Other values (14)14
58.3%

Most occurring characters

ValueCountFrequency (%)
/168
 
9.7%
a144
 
8.3%
s120
 
6.9%
m120
 
6.9%
t120
 
6.9%
p96
 
5.6%
e96
 
5.6%
i72
 
4.2%
c72
 
4.2%
.72
 
4.2%
Other values (22)648
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1224
70.8%
Other Punctuation264
 
15.3%
Decimal Number216
 
12.5%
Connector Punctuation24
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a144
11.8%
s120
9.8%
m120
9.8%
t120
9.8%
p96
 
7.8%
e96
 
7.8%
i72
 
5.9%
c72
 
5.9%
d72
 
5.9%
l48
 
3.9%
Other values (8)264
21.6%
Decimal Number
ValueCountFrequency (%)
244
20.4%
736
16.7%
827
12.5%
922
10.2%
321
9.7%
618
8.3%
117
 
7.9%
015
 
6.9%
511
 
5.1%
45
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/168
63.6%
.72
27.3%
:24
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1224
70.8%
Common504
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a144
11.8%
s120
9.8%
m120
9.8%
t120
9.8%
p96
 
7.8%
e96
 
7.8%
i72
 
5.9%
c72
 
5.9%
d72
 
5.9%
l48
 
3.9%
Other values (8)264
21.6%
Common
ValueCountFrequency (%)
/168
33.3%
.72
14.3%
244
 
8.7%
736
 
7.1%
827
 
5.4%
_24
 
4.8%
:24
 
4.8%
922
 
4.4%
321
 
4.2%
618
 
3.6%
Other values (4)48
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/168
 
9.7%
a144
 
8.3%
s120
 
6.9%
m120
 
6.9%
t120
 
6.9%
p96
 
5.6%
e96
 
5.6%
i72
 
4.2%
c72
 
4.2%
.72
 
4.2%
Other values (22)648
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct24
Distinct (%)100.0%
Missing64
Missing (%)72.7%
Memory size832.0 B
https://static.tvmaze.com/uploads/images/original_untouched/360/901422.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/720303.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/382/956556.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/286/716334.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/375/937751.jpg
 
1
Other values (19)
19 

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters1776
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/360/901422.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719751.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719752.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726343.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726859.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/360/901422.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/288/720303.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/382/956556.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/286/716334.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/375/937751.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/311/778162.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719832.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719831.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719830.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719828.jpg1
 
1.1%
Other values (14)14
 
15.9%
(Missing)64
72.7%

Length

2022-09-05T21:40:10.354035image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/360/901422.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/288/720303.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/719751.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/719752.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726343.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726859.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726860.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726861.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726862.jpg1
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726863.jpg1
 
4.2%
Other values (14)14
58.3%

Most occurring characters

ValueCountFrequency (%)
/168
 
9.5%
t144
 
8.1%
a120
 
6.8%
s96
 
5.4%
i96
 
5.4%
o96
 
5.4%
p72
 
4.1%
c72
 
4.1%
.72
 
4.1%
g72
 
4.1%
Other values (23)768
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1272
71.6%
Other Punctuation264
 
14.9%
Decimal Number216
 
12.2%
Connector Punctuation24
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t144
 
11.3%
a120
 
9.4%
s96
 
7.5%
i96
 
7.5%
o96
 
7.5%
p72
 
5.7%
c72
 
5.7%
g72
 
5.7%
m72
 
5.7%
e72
 
5.7%
Other values (9)360
28.3%
Decimal Number
ValueCountFrequency (%)
244
20.4%
736
16.7%
827
12.5%
922
10.2%
321
9.7%
618
8.3%
117
 
7.9%
015
 
6.9%
511
 
5.1%
45
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/168
63.6%
.72
27.3%
:24
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1272
71.6%
Common504
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t144
 
11.3%
a120
 
9.4%
s96
 
7.5%
i96
 
7.5%
o96
 
7.5%
p72
 
5.7%
c72
 
5.7%
g72
 
5.7%
m72
 
5.7%
e72
 
5.7%
Other values (9)360
28.3%
Common
ValueCountFrequency (%)
/168
33.3%
.72
14.3%
244
 
8.7%
736
 
7.1%
827
 
5.4%
:24
 
4.8%
_24
 
4.8%
922
 
4.4%
321
 
4.2%
618
 
3.6%
Other values (4)48
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1776
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/168
 
9.5%
t144
 
8.1%
a120
 
6.8%
s96
 
5.4%
i96
 
5.4%
o96
 
5.4%
p72
 
4.1%
c72
 
4.1%
.72
 
4.1%
g72
 
4.1%
Other values (23)768
43.2%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size832.0 B
https://api.tvmaze.com/episodes/2179612
 
1
https://api.tvmaze.com/episodes/1986871
 
1
https://api.tvmaze.com/episodes/1985464
 
1
https://api.tvmaze.com/episodes/1985463
 
1
https://api.tvmaze.com/episodes/1984949
 
1
Other values (83)
83 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3432
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2179612
2nd rowhttps://api.tvmaze.com/episodes/1986871
3rd rowhttps://api.tvmaze.com/episodes/1983257
4th rowhttps://api.tvmaze.com/episodes/1983258
5th rowhttps://api.tvmaze.com/episodes/1971569

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21796121
 
1.1%
https://api.tvmaze.com/episodes/19868711
 
1.1%
https://api.tvmaze.com/episodes/19854641
 
1.1%
https://api.tvmaze.com/episodes/19854631
 
1.1%
https://api.tvmaze.com/episodes/19849491
 
1.1%
https://api.tvmaze.com/episodes/19849481
 
1.1%
https://api.tvmaze.com/episodes/19776391
 
1.1%
https://api.tvmaze.com/episodes/19776381
 
1.1%
https://api.tvmaze.com/episodes/19761941
 
1.1%
https://api.tvmaze.com/episodes/19761931
 
1.1%
Other values (78)78
88.6%

Length

2022-09-05T21:40:10.431431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21796121
 
1.1%
https://api.tvmaze.com/episodes/19868711
 
1.1%
https://api.tvmaze.com/episodes/19832571
 
1.1%
https://api.tvmaze.com/episodes/19832581
 
1.1%
https://api.tvmaze.com/episodes/19715691
 
1.1%
https://api.tvmaze.com/episodes/19850441
 
1.1%
https://api.tvmaze.com/episodes/23861051
 
1.1%
https://api.tvmaze.com/episodes/19856161
 
1.1%
https://api.tvmaze.com/episodes/20962961
 
1.1%
https://api.tvmaze.com/episodes/20300191
 
1.1%
Other values (78)78
88.6%

Most occurring characters

ValueCountFrequency (%)
/352
 
10.3%
p264
 
7.7%
s264
 
7.7%
e264
 
7.7%
t264
 
7.7%
o176
 
5.1%
a176
 
5.1%
i176
 
5.1%
.176
 
5.1%
m176
 
5.1%
Other values (16)1144
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2200
64.1%
Other Punctuation616
 
17.9%
Decimal Number616
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p264
12.0%
s264
12.0%
e264
12.0%
t264
12.0%
o176
8.0%
a176
8.0%
i176
8.0%
m176
8.0%
h88
 
4.0%
d88
 
4.0%
Other values (3)264
12.0%
Decimal Number
ValueCountFrequency (%)
1115
18.7%
9104
16.9%
261
9.9%
354
8.8%
650
8.1%
749
8.0%
049
8.0%
847
7.6%
444
 
7.1%
543
 
7.0%
Other Punctuation
ValueCountFrequency (%)
/352
57.1%
.176
28.6%
:88
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2200
64.1%
Common1232
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/352
28.6%
.176
14.3%
1115
 
9.3%
9104
 
8.4%
:88
 
7.1%
261
 
5.0%
354
 
4.4%
650
 
4.1%
749
 
4.0%
049
 
4.0%
Other values (3)134
 
10.9%
Latin
ValueCountFrequency (%)
p264
12.0%
s264
12.0%
e264
12.0%
t264
12.0%
o176
8.0%
a176
8.0%
i176
8.0%
m176
8.0%
h88
 
4.0%
d88
 
4.0%
Other values (3)264
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/352
 
10.3%
p264
 
7.7%
s264
 
7.7%
e264
 
7.7%
t264
 
7.7%
o176
 
5.1%
a176
 
5.1%
i176
 
5.1%
.176
 
5.1%
m176
 
5.1%
Other values (16)1144
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct67
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47043.55682
Minimum2266
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:10.535998image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2266
5-th percentile17925.05
Q145155
median51992
Q352639
95-th percentile57860.6
Maximum61755
Range59489
Interquartile range (IQR)7484

Descriptive statistics

Standard deviation11802.48254
Coefficient of variation (CV)0.2508841452
Kurtosis4.800320001
Mean47043.55682
Median Absolute Deviation (MAD)3418
Skewness-2.171789951
Sum4139833
Variance139298594.1
MonotonicityNot monotonic
2022-09-05T21:40:10.660684image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
526395
 
5.7%
451554
 
4.5%
519924
 
4.5%
521082
 
2.3%
586892
 
2.3%
152502
 
2.3%
527802
 
2.3%
524212
 
2.3%
524002
 
2.3%
521592
 
2.3%
Other values (57)61
69.3%
ValueCountFrequency (%)
22661
1.1%
25041
1.1%
129061
1.1%
152502
2.3%
228931
1.1%
262681
1.1%
270551
1.1%
283461
1.1%
339441
1.1%
340601
1.1%
ValueCountFrequency (%)
617551
1.1%
586892
2.3%
583671
1.1%
579531
1.1%
576891
1.1%
574781
1.1%
570302
2.3%
567461
1.1%
565311
1.1%
559191
1.1%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct67
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size832.0 B
https://www.tvmaze.com/shows/52639/puckers
 
5
https://www.tvmaze.com/shows/45155/canal-boat-diaries
 
4
https://www.tvmaze.com/shows/51992/the-surgeons-cut
 
4
https://www.tvmaze.com/shows/52108/psych-hunter
 
2
https://www.tvmaze.com/shows/58689/my-supernatural-power
 
2
Other values (62)
71 

Length

Max length74
Median length60.5
Mean length50.17045455
Min length41

Characters and Unicode

Total characters4415
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)60.2%

Sample

1st rowhttps://www.tvmaze.com/shows/49630/kontakty
2nd rowhttps://www.tvmaze.com/shows/52198/kotiki
3rd rowhttps://www.tvmaze.com/shows/52316/mertvye-dusi
4th rowhttps://www.tvmaze.com/shows/52316/mertvye-dusi
5th rowhttps://www.tvmaze.com/shows/47207/mermaid-prince

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52639/puckers5
 
5.7%
https://www.tvmaze.com/shows/45155/canal-boat-diaries4
 
4.5%
https://www.tvmaze.com/shows/51992/the-surgeons-cut4
 
4.5%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
2.3%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
2.3%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.3%
https://www.tvmaze.com/shows/52780/mermaid-prince2
 
2.3%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
2.3%
https://www.tvmaze.com/shows/52400/dream-detective2
 
2.3%
https://www.tvmaze.com/shows/52159/to-love2
 
2.3%
Other values (57)61
69.3%

Length

2022-09-05T21:40:10.786803image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52639/puckers5
 
5.7%
https://www.tvmaze.com/shows/51992/the-surgeons-cut4
 
4.5%
https://www.tvmaze.com/shows/45155/canal-boat-diaries4
 
4.5%
https://www.tvmaze.com/shows/52400/dream-detective2
 
2.3%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.3%
https://www.tvmaze.com/shows/52107/new-face2
 
2.3%
https://www.tvmaze.com/shows/57030/gjor-det-sjol2
 
2.3%
https://www.tvmaze.com/shows/52159/to-love2
 
2.3%
https://www.tvmaze.com/shows/52316/mertvye-dusi2
 
2.3%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
2.3%
Other values (57)61
69.3%

Most occurring characters

ValueCountFrequency (%)
/440
 
10.0%
w366
 
8.3%
t351
 
8.0%
s350
 
7.9%
o253
 
5.7%
e232
 
5.3%
h220
 
5.0%
m220
 
5.0%
a181
 
4.1%
.176
 
4.0%
Other values (29)1626
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3112
70.5%
Other Punctuation704
 
15.9%
Decimal Number445
 
10.1%
Dash Punctuation154
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w366
11.8%
t351
11.3%
s350
11.2%
o253
 
8.1%
e232
 
7.5%
h220
 
7.1%
m220
 
7.1%
a181
 
5.8%
c128
 
4.1%
p114
 
3.7%
Other values (15)697
22.4%
Decimal Number
ValueCountFrequency (%)
588
19.8%
254
12.1%
451
11.5%
142
9.4%
041
9.2%
939
8.8%
336
8.1%
634
 
7.6%
733
 
7.4%
827
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/440
62.5%
.176
 
25.0%
:88
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3112
70.5%
Common1303
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w366
11.8%
t351
11.3%
s350
11.2%
o253
 
8.1%
e232
 
7.5%
h220
 
7.1%
m220
 
7.1%
a181
 
5.8%
c128
 
4.1%
p114
 
3.7%
Other values (15)697
22.4%
Common
ValueCountFrequency (%)
/440
33.8%
.176
 
13.5%
-154
 
11.8%
588
 
6.8%
:88
 
6.8%
254
 
4.1%
451
 
3.9%
142
 
3.2%
041
 
3.1%
939
 
3.0%
Other values (4)130
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/440
 
10.0%
w366
 
8.3%
t351
 
8.0%
s350
 
7.9%
o253
 
5.7%
e232
 
5.3%
h220
 
5.0%
m220
 
5.0%
a181
 
4.1%
.176
 
4.0%
Other values (29)1626
36.8%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct66
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size832.0 B
Puckers
 
5
Canal Boat Diaries
 
4
The Surgeon's Cut
 
4
Mermaid Prince
 
3
New Face
 
2
Other values (61)
70 

Length

Max length40
Median length26
Mean length15.44318182
Min length6

Characters and Unicode

Total characters1359
Distinct characters99
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)59.1%

Sample

1st rowКонтакты
2nd rowКотики
3rd rowМёртвые души
4th rowМёртвые души
5th rowMermaid Prince

Common Values

ValueCountFrequency (%)
Puckers5
 
5.7%
Canal Boat Diaries4
 
4.5%
The Surgeon's Cut4
 
4.5%
Mermaid Prince3
 
3.4%
New Face2
 
2.3%
My Supernatural Power2
 
2.3%
The Young Turks2
 
2.3%
You Complete Me2
 
2.3%
Dream Detective2
 
2.3%
To Love2
 
2.3%
Other values (56)60
68.2%

Length

2022-09-05T21:40:10.906601image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the13
 
5.3%
puckers5
 
2.1%
cut4
 
1.6%
of4
 
1.6%
love4
 
1.6%
canal4
 
1.6%
surgeon's4
 
1.6%
diaries4
 
1.6%
boat4
 
1.6%
prince3
 
1.2%
Other values (162)194
79.8%

Most occurring characters

ValueCountFrequency (%)
155
 
11.4%
e129
 
9.5%
a77
 
5.7%
n64
 
4.7%
r64
 
4.7%
i61
 
4.5%
o58
 
4.3%
s55
 
4.0%
t53
 
3.9%
u49
 
3.6%
Other values (89)594
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter960
70.6%
Uppercase Letter217
 
16.0%
Space Separator155
 
11.4%
Other Punctuation17
 
1.3%
Decimal Number7
 
0.5%
Currency Symbol2
 
0.1%
Close Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e129
13.4%
a77
 
8.0%
n64
 
6.7%
r64
 
6.7%
i61
 
6.4%
o58
 
6.0%
s55
 
5.7%
t53
 
5.5%
u49
 
5.1%
l37
 
3.9%
Other values (42)313
32.6%
Uppercase Letter
ValueCountFrequency (%)
T24
 
11.1%
S22
 
10.1%
C18
 
8.3%
M17
 
7.8%
P14
 
6.5%
B12
 
5.5%
D12
 
5.5%
Y11
 
5.1%
F9
 
4.1%
L8
 
3.7%
Other values (21)70
32.3%
Other Punctuation
ValueCountFrequency (%)
'7
41.2%
:4
23.5%
.1
 
5.9%
&1
 
5.9%
,1
 
5.9%
?1
 
5.9%
@1
 
5.9%
#1
 
5.9%
Decimal Number
ValueCountFrequency (%)
03
42.9%
22
28.6%
11
 
14.3%
51
 
14.3%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1056
77.7%
Common182
 
13.4%
Cyrillic121
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e129
 
12.2%
a77
 
7.3%
n64
 
6.1%
r64
 
6.1%
i61
 
5.8%
o58
 
5.5%
s55
 
5.2%
t53
 
5.0%
u49
 
4.6%
l37
 
3.5%
Other values (39)409
38.7%
Cyrillic
ValueCountFrequency (%)
о10
 
8.3%
т10
 
8.3%
р9
 
7.4%
и8
 
6.6%
к8
 
6.6%
а8
 
6.6%
е8
 
6.6%
у5
 
4.1%
н4
 
3.3%
з4
 
3.3%
Other values (24)47
38.8%
Common
ValueCountFrequency (%)
155
85.2%
'7
 
3.8%
:4
 
2.2%
03
 
1.6%
22
 
1.1%
11
 
0.5%
.1
 
0.5%
51
 
0.5%
&1
 
0.5%
,1
 
0.5%
Other values (6)6
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1230
90.5%
Cyrillic121
 
8.9%
None7
 
0.5%
Currency Symbols1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
 
12.6%
e129
 
10.5%
a77
 
6.3%
n64
 
5.2%
r64
 
5.2%
i61
 
5.0%
o58
 
4.7%
s55
 
4.5%
t53
 
4.3%
u49
 
4.0%
Other values (53)465
37.8%
Cyrillic
ValueCountFrequency (%)
о10
 
8.3%
т10
 
8.3%
р9
 
7.4%
и8
 
6.6%
к8
 
6.6%
а8
 
6.6%
е8
 
6.6%
у5
 
4.1%
н4
 
3.3%
з4
 
3.3%
Other values (24)47
38.8%
None
ValueCountFrequency (%)
ø7
100.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size832.0 B
Scripted
34 
Documentary
13 
Animation
11 
Talk Show
11 
Reality
Other values (4)
10 

Length

Max length11
Median length9
Mean length8.454545455
Min length4

Characters and Unicode

Total characters744
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowGame Show
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted34
38.6%
Documentary13
 
14.8%
Animation11
 
12.5%
Talk Show11
 
12.5%
Reality9
 
10.2%
Game Show4
 
4.5%
News3
 
3.4%
Variety2
 
2.3%
Sports1
 
1.1%

Length

2022-09-05T21:40:11.012432image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:11.121645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted34
33.0%
show15
14.6%
documentary13
 
12.6%
animation11
 
10.7%
talk11
 
10.7%
reality9
 
8.7%
game4
 
3.9%
news3
 
2.9%
variety2
 
1.9%
sports1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
t70
 
9.4%
i67
 
9.0%
e65
 
8.7%
S50
 
6.7%
a50
 
6.7%
r50
 
6.7%
c47
 
6.3%
o40
 
5.4%
p35
 
4.7%
n35
 
4.7%
Other values (17)235
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter626
84.1%
Uppercase Letter103
 
13.8%
Space Separator15
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t70
11.2%
i67
10.7%
e65
10.4%
a50
 
8.0%
r50
 
8.0%
c47
 
7.5%
o40
 
6.4%
p35
 
5.6%
n35
 
5.6%
d34
 
5.4%
Other values (8)133
21.2%
Uppercase Letter
ValueCountFrequency (%)
S50
48.5%
D13
 
12.6%
T11
 
10.7%
A11
 
10.7%
R9
 
8.7%
G4
 
3.9%
N3
 
2.9%
V2
 
1.9%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin729
98.0%
Common15
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t70
 
9.6%
i67
 
9.2%
e65
 
8.9%
S50
 
6.9%
a50
 
6.9%
r50
 
6.9%
c47
 
6.4%
o40
 
5.5%
p35
 
4.8%
n35
 
4.8%
Other values (16)220
30.2%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII744
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t70
 
9.4%
i67
 
9.0%
e65
 
8.7%
S50
 
6.7%
a50
 
6.7%
r50
 
6.7%
c47
 
6.3%
o40
 
5.4%
p35
 
4.7%
n35
 
4.7%
Other values (17)235
31.6%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)18.6%
Missing2
Missing (%)2.3%
Memory size832.0 B
English
23 
Chinese
22 
Norwegian
13 
Russian
Thai
Other values (11)
16 

Length

Max length10
Median length7
Mean length7.162790698
Min length4

Characters and Unicode

Total characters616
Distinct characters33
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)9.3%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowKorean

Common Values

ValueCountFrequency (%)
English23
26.1%
Chinese22
25.0%
Norwegian13
14.8%
Russian8
 
9.1%
Thai4
 
4.5%
Arabic3
 
3.4%
Korean3
 
3.4%
Ukrainian2
 
2.3%
Dutch1
 
1.1%
Portuguese1
 
1.1%
Other values (6)6
 
6.8%
(Missing)2
 
2.3%

Length

2022-09-05T21:40:11.217931image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english23
26.7%
chinese22
25.6%
norwegian13
15.1%
russian8
 
9.3%
thai4
 
4.7%
arabic3
 
3.5%
korean3
 
3.5%
ukrainian2
 
2.3%
dutch1
 
1.2%
portuguese1
 
1.2%
Other values (6)6
 
7.0%

Most occurring characters

ValueCountFrequency (%)
i80
13.0%
n78
12.7%
e66
10.7%
s65
10.6%
h54
8.8%
a42
 
6.8%
g38
 
6.2%
r24
 
3.9%
E23
 
3.7%
l23
 
3.7%
Other values (23)123
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter530
86.0%
Uppercase Letter86
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i80
15.1%
n78
14.7%
e66
12.5%
s65
12.3%
h54
10.2%
a42
7.9%
g38
7.2%
r24
 
4.5%
l23
 
4.3%
o17
 
3.2%
Other values (9)43
8.1%
Uppercase Letter
ValueCountFrequency (%)
E23
26.7%
C22
25.6%
N13
15.1%
R8
 
9.3%
K4
 
4.7%
T4
 
4.7%
A3
 
3.5%
U2
 
2.3%
S2
 
2.3%
D1
 
1.2%
Other values (4)4
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Latin616
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i80
13.0%
n78
12.7%
e66
10.7%
s65
10.6%
h54
8.8%
a42
 
6.8%
g38
 
6.2%
r24
 
3.9%
E23
 
3.7%
l23
 
3.7%
Other values (23)123
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i80
13.0%
n78
12.7%
e66
10.7%
s65
10.6%
h54
8.8%
a42
 
6.8%
g38
 
6.2%
r24
 
3.9%
E23
 
3.7%
l23
 
3.7%
Other values (23)123
20.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size832.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size832.0 B
Running
40 
Ended
38 
To Be Determined
10 

Length

Max length16
Median length7
Mean length7.159090909
Min length5

Characters and Unicode

Total characters630
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Running40
45.5%
Ended38
43.2%
To Be Determined10
 
11.4%

Length

2022-09-05T21:40:11.307624image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:11.402808image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running40
37.0%
ended38
35.2%
to10
 
9.3%
be10
 
9.3%
determined10
 
9.3%

Most occurring characters

ValueCountFrequency (%)
n168
26.7%
d86
13.7%
e78
12.4%
i50
 
7.9%
R40
 
6.3%
u40
 
6.3%
g40
 
6.3%
E38
 
6.0%
20
 
3.2%
T10
 
1.6%
Other values (6)60
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter502
79.7%
Uppercase Letter108
 
17.1%
Space Separator20
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n168
33.5%
d86
17.1%
e78
15.5%
i50
 
10.0%
u40
 
8.0%
g40
 
8.0%
o10
 
2.0%
t10
 
2.0%
r10
 
2.0%
m10
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
R40
37.0%
E38
35.2%
T10
 
9.3%
B10
 
9.3%
D10
 
9.3%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin610
96.8%
Common20
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n168
27.5%
d86
14.1%
e78
12.8%
i50
 
8.2%
R40
 
6.6%
u40
 
6.6%
g40
 
6.6%
E38
 
6.2%
T10
 
1.6%
o10
 
1.6%
Other values (5)50
 
8.2%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n168
26.7%
d86
13.7%
e78
12.4%
i50
 
7.9%
R40
 
6.3%
u40
 
6.3%
g40
 
6.3%
E38
 
6.0%
20
 
3.2%
T10
 
1.6%
Other values (6)60
 
9.5%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct19
Distinct (%)29.2%
Missing23
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean38.32307692
Minimum2
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:11.476369image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.6
Q125
median30
Q345
95-th percentile90
Maximum120
Range118
Interquartile range (IQR)20

Descriptive statistics

Standard deviation25.24263983
Coefficient of variation (CV)0.6586798831
Kurtosis3.535780738
Mean38.32307692
Median Absolute Deviation (MAD)15
Skewness1.641579608
Sum2491
Variance637.1908654
MonotonicityNot monotonic
2022-09-05T21:40:11.570195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4517
19.3%
3014
15.9%
604
 
4.5%
254
 
4.5%
204
 
4.5%
123
 
3.4%
1203
 
3.4%
52
 
2.3%
152
 
2.3%
432
 
2.3%
Other values (9)10
11.4%
(Missing)23
26.1%
ValueCountFrequency (%)
21
 
1.1%
41
 
1.1%
52
2.3%
81
 
1.1%
123
3.4%
152
2.3%
191
 
1.1%
204
4.5%
231
 
1.1%
254
4.5%
ValueCountFrequency (%)
1203
 
3.4%
902
 
2.3%
604
 
4.5%
551
 
1.1%
4517
19.3%
432
 
2.3%
401
 
1.1%
331
 
1.1%
3014
15.9%
254
 
4.5%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)38.8%
Missing3
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean35.96470588
Minimum2
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:11.660288image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q120
median31
Q345
95-th percentile87.4
Maximum120
Range118
Interquartile range (IQR)25

Descriptive statistics

Standard deviation24.39137585
Coefficient of variation (CV)0.678203123
Kurtosis2.826998301
Mean35.96470588
Median Absolute Deviation (MAD)14
Skewness1.39097967
Sum3057
Variance594.9392157
MonotonicityNot monotonic
2022-09-05T21:40:11.766361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4516
18.2%
307
 
8.0%
315
 
5.7%
205
 
5.7%
54
 
4.5%
604
 
4.5%
254
 
4.5%
124
 
4.5%
544
 
4.5%
433
 
3.4%
Other values (23)29
33.0%
(Missing)3
 
3.4%
ValueCountFrequency (%)
21
 
1.1%
41
 
1.1%
54
4.5%
61
 
1.1%
72
2.3%
112
2.3%
124
4.5%
131
 
1.1%
141
 
1.1%
152
2.3%
ValueCountFrequency (%)
1202
 
2.3%
1101
 
1.1%
911
 
1.1%
901
 
1.1%
771
 
1.1%
604
 
4.5%
591
 
1.1%
544
 
4.5%
4516
18.2%
433
 
3.4%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct59
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size832.0 B
2020-12-09
12 
2020-11-23
 
4
2019-11-18
 
4
2020-12-08
 
3
2020-11-18
 
3
Other values (54)
62 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters880
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)52.3%

Sample

1st row2019-04-03
2nd row2020-11-30
3rd row2020-12-09
4th row2020-12-09
5th row2020-04-14

Common Values

ValueCountFrequency (%)
2020-12-0912
 
13.6%
2020-11-234
 
4.5%
2019-11-184
 
4.5%
2020-12-083
 
3.4%
2020-11-183
 
3.4%
2020-11-192
 
2.3%
2020-12-022
 
2.3%
2013-12-242
 
2.3%
2020-07-082
 
2.3%
2020-11-042
 
2.3%
Other values (49)52
59.1%

Length

2022-09-05T21:40:11.851946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0912
 
13.6%
2019-11-184
 
4.5%
2020-11-234
 
4.5%
2020-12-083
 
3.4%
2020-11-183
 
3.4%
2020-11-042
 
2.3%
2020-11-302
 
2.3%
2020-11-252
 
2.3%
2020-11-242
 
2.3%
2020-07-082
 
2.3%
Other values (49)52
59.1%

Most occurring characters

ValueCountFrequency (%)
0224
25.5%
2195
22.2%
-176
20.0%
1150
17.0%
941
 
4.7%
825
 
2.8%
421
 
2.4%
316
 
1.8%
713
 
1.5%
510
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number704
80.0%
Dash Punctuation176
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0224
31.8%
2195
27.7%
1150
21.3%
941
 
5.8%
825
 
3.6%
421
 
3.0%
316
 
2.3%
713
 
1.8%
510
 
1.4%
69
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
-176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0224
25.5%
2195
22.2%
-176
20.0%
1150
17.0%
941
 
4.7%
825
 
2.8%
421
 
2.4%
316
 
1.8%
713
 
1.5%
510
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0224
25.5%
2195
22.2%
-176
20.0%
1150
17.0%
941
 
4.7%
825
 
2.8%
421
 
2.4%
316
 
1.8%
713
 
1.5%
510
 
1.1%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)42.1%
Missing50
Missing (%)56.8%
Memory size832.0 B
2020-12-09
2020-12-16
2020-12-30
2021-01-27
2020-12-22
Other values (11)
14 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters380
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)21.1%

Sample

1st row2020-12-11
2nd row2020-12-16
3rd row2020-12-16
4th row2020-12-10
5th row2021-01-06

Common Values

ValueCountFrequency (%)
2020-12-098
 
9.1%
2020-12-167
 
8.0%
2020-12-305
 
5.7%
2021-01-272
 
2.3%
2020-12-222
 
2.3%
2020-12-232
 
2.3%
2021-01-052
 
2.3%
2021-01-142
 
2.3%
2020-12-101
 
1.1%
2021-01-061
 
1.1%
Other values (6)6
 
6.8%
(Missing)50
56.8%

Length

2022-09-05T21:40:11.932659image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-098
21.1%
2020-12-167
18.4%
2020-12-305
13.2%
2021-01-272
 
5.3%
2020-12-222
 
5.3%
2020-12-232
 
5.3%
2021-01-052
 
5.3%
2021-01-142
 
5.3%
2020-12-101
 
2.6%
2021-01-061
 
2.6%
Other values (6)6
15.8%

Most occurring characters

ValueCountFrequency (%)
2116
30.5%
094
24.7%
-76
20.0%
158
15.3%
910
 
2.6%
69
 
2.4%
38
 
2.1%
53
 
0.8%
43
 
0.8%
72
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number304
80.0%
Dash Punctuation76
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2116
38.2%
094
30.9%
158
19.1%
910
 
3.3%
69
 
3.0%
38
 
2.6%
53
 
1.0%
43
 
1.0%
72
 
0.7%
81
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2116
30.5%
094
24.7%
-76
20.0%
158
15.3%
910
 
2.6%
69
 
2.4%
38
 
2.1%
53
 
0.8%
43
 
0.8%
72
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2116
30.5%
094
24.7%
-76
20.0%
158
15.3%
910
 
2.6%
69
 
2.4%
38
 
2.1%
53
 
0.8%
43
 
0.8%
72
 
0.5%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct57
Distinct (%)76.0%
Missing13
Missing (%)14.8%
Memory size832.0 B
https://tv.nrk.no/serie/puckers
 
5
https://www.netflix.com/title/81004466
 
4
https://www.bbc.co.uk/programmes/m000bks0
 
4
https://www.iqiyi.com/a_19rrhskr95.html
 
2
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=1
 
2
Other values (52)
58 

Length

Max length250
Median length70
Mean length50.02666667
Min length18

Characters and Unicode

Total characters3752
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)61.3%

Sample

1st rowhttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI
2nd rowhttp://epic-media.ru/project/kotiki
3rd rowhttps://www.ivi.ru/watch/mertvyie-dushi-2020
4th rowhttps://www.ivi.ru/watch/mertvyie-dushi-2020
5th rowhttps://v.qq.com/detail/a/awnia0n2erqryf3.html

Common Values

ValueCountFrequency (%)
https://tv.nrk.no/serie/puckers5
 
5.7%
https://www.netflix.com/title/810044664
 
4.5%
https://www.bbc.co.uk/programmes/m000bks04
 
4.5%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.3%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.3%
https://www.tytnetwork.com2
 
2.3%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.3%
https://tv.nrk.no/serie/gjoer-det-sjoel2
 
2.3%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.3%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.3%
Other values (47)48
54.5%
(Missing)13
 
14.8%

Length

2022-09-05T21:40:12.042550image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://tv.nrk.no/serie/puckers5
 
6.7%
https://www.bbc.co.uk/programmes/m000bks04
 
5.3%
https://www.netflix.com/title/810044664
 
5.3%
https://tv.nrk.no/serie/gjoer-det-sjoel2
 
2.7%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.7%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.7%
https://www.ivi.ru/watch/mertvyie-dushi-20202
 
2.7%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.7%
https://www.tytnetwork.com2
 
2.7%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.7%
Other values (47)48
64.0%

Most occurring characters

ValueCountFrequency (%)
/310
 
8.3%
t286
 
7.6%
s189
 
5.0%
e178
 
4.7%
.154
 
4.1%
o147
 
3.9%
h139
 
3.7%
%131
 
3.5%
w127
 
3.4%
r125
 
3.3%
Other values (64)1966
52.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2353
62.7%
Other Punctuation686
 
18.3%
Decimal Number390
 
10.4%
Uppercase Letter248
 
6.6%
Dash Punctuation46
 
1.2%
Math Symbol16
 
0.4%
Connector Punctuation13
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t286
 
12.2%
s189
 
8.0%
e178
 
7.6%
o147
 
6.2%
h139
 
5.9%
w127
 
5.4%
r125
 
5.3%
p120
 
5.1%
m118
 
5.0%
i115
 
4.9%
Other values (16)809
34.4%
Uppercase Letter
ValueCountFrequency (%)
E48
19.4%
B47
19.0%
A23
 
9.3%
Y10
 
4.0%
C10
 
4.0%
Q9
 
3.6%
P8
 
3.2%
S8
 
3.2%
H7
 
2.8%
F7
 
2.8%
Other values (16)71
28.6%
Decimal Number
ValueCountFrequency (%)
092
23.6%
864
16.4%
943
11.0%
133
 
8.5%
432
 
8.2%
629
 
7.4%
529
 
7.4%
229
 
7.4%
721
 
5.4%
318
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/310
45.2%
.154
22.4%
%131
19.1%
:75
 
10.9%
?9
 
1.3%
&5
 
0.7%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=14
87.5%
+2
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-46
100.0%
Connector Punctuation
ValueCountFrequency (%)
_13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2601
69.3%
Common1151
30.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t286
 
11.0%
s189
 
7.3%
e178
 
6.8%
o147
 
5.7%
h139
 
5.3%
w127
 
4.9%
r125
 
4.8%
p120
 
4.6%
m118
 
4.5%
i115
 
4.4%
Other values (42)1057
40.6%
Common
ValueCountFrequency (%)
/310
26.9%
.154
13.4%
%131
11.4%
092
 
8.0%
:75
 
6.5%
864
 
5.6%
-46
 
4.0%
943
 
3.7%
133
 
2.9%
432
 
2.8%
Other values (12)171
14.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/310
 
8.3%
t286
 
7.6%
s189
 
5.0%
e178
 
4.7%
.154
 
4.1%
o147
 
3.9%
h139
 
3.7%
%131
 
3.5%
w127
 
3.4%
r125
 
3.3%
Other values (64)1966
52.4%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size832.0 B
49 
20:00
13 
06:00
10:00
19:30
 
4
Other values (8)
11 

Length

Max length5
Median length0
Mean length2.215909091
Min length0

Characters and Unicode

Total characters195
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)5.7%

Sample

1st row
2nd row10:00
3rd row
4th row
5th row11:00

Common Values

ValueCountFrequency (%)
49
55.7%
20:0013
 
14.8%
06:006
 
6.8%
10:005
 
5.7%
19:304
 
4.5%
21:002
 
2.3%
00:002
 
2.3%
19:002
 
2.3%
11:001
 
1.1%
12:001
 
1.1%
Other values (3)3
 
3.4%

Length

2022-09-05T21:40:12.138190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0013
33.3%
06:006
15.4%
10:005
 
12.8%
19:304
 
10.3%
21:002
 
5.1%
00:002
 
5.1%
19:002
 
5.1%
11:001
 
2.6%
12:001
 
2.6%
17:351
 
2.6%
Other values (2)2
 
5.1%

Most occurring characters

ValueCountFrequency (%)
098
50.3%
:39
 
20.0%
119
 
9.7%
218
 
9.2%
66
 
3.1%
96
 
3.1%
35
 
2.6%
52
 
1.0%
71
 
0.5%
41
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number156
80.0%
Other Punctuation39
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
098
62.8%
119
 
12.2%
218
 
11.5%
66
 
3.8%
96
 
3.8%
35
 
3.2%
52
 
1.3%
71
 
0.6%
41
 
0.6%
Other Punctuation
ValueCountFrequency (%)
:39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
098
50.3%
:39
 
20.0%
119
 
9.7%
218
 
9.2%
66
 
3.1%
96
 
3.1%
35
 
2.6%
52
 
1.0%
71
 
0.5%
41
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
098
50.3%
:39
 
20.0%
119
 
9.7%
218
 
9.2%
66
 
3.1%
96
 
3.1%
35
 
2.6%
52
 
1.0%
71
 
0.5%
41
 
0.5%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size832.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing82
Missing (%)93.2%
Memory size832.0 B
7.2
5.0
6.9
7.0
8.2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters18
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row7.2
2nd row5.0
3rd row6.9
4th row7.0
5th row8.2

Common Values

ValueCountFrequency (%)
7.22
 
2.3%
5.01
 
1.1%
6.91
 
1.1%
7.01
 
1.1%
8.21
 
1.1%
(Missing)82
93.2%

Length

2022-09-05T21:40:12.217843image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:12.305772image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.22
33.3%
5.01
16.7%
6.91
16.7%
7.01
16.7%
8.21
16.7%

Most occurring characters

ValueCountFrequency (%)
.6
33.3%
73
16.7%
23
16.7%
02
 
11.1%
51
 
5.6%
61
 
5.6%
91
 
5.6%
81
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
66.7%
Other Punctuation6
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
73
25.0%
23
25.0%
02
16.7%
51
 
8.3%
61
 
8.3%
91
 
8.3%
81
 
8.3%
Other Punctuation
ValueCountFrequency (%)
.6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.6
33.3%
73
16.7%
23
16.7%
02
 
11.1%
51
 
5.6%
61
 
5.6%
91
 
5.6%
81
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.6
33.3%
73
16.7%
23
16.7%
02
 
11.1%
51
 
5.6%
61
 
5.6%
91
 
5.6%
81
 
5.6%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct42
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.23863636
Minimum3
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:12.398728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q113.75
median22
Q345.5
95-th percentile78
Maximum92
Range89
Interquartile range (IQR)31.75

Descriptive statistics

Standard deviation23.42019676
Coefficient of variation (CV)0.7745123319
Kurtosis-0.03196924586
Mean30.23863636
Median Absolute Deviation (MAD)13.5
Skewness0.9544606131
Sum2661
Variance548.5056165
MonotonicityNot monotonic
2022-09-05T21:40:12.510641image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
217
 
8.0%
36
 
6.8%
75
 
5.7%
224
 
4.5%
244
 
4.5%
534
 
4.5%
674
 
4.5%
204
 
4.5%
233
 
3.4%
153
 
3.4%
Other values (32)44
50.0%
ValueCountFrequency (%)
36
6.8%
42
 
2.3%
51
 
1.1%
61
 
1.1%
75
5.7%
82
 
2.3%
91
 
1.1%
101
 
1.1%
112
 
2.3%
131
 
1.1%
ValueCountFrequency (%)
921
 
1.1%
862
2.3%
831
 
1.1%
782
2.3%
721
 
1.1%
674
4.5%
621
 
1.1%
611
 
1.1%
591
 
1.1%
561
 
1.1%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)32.9%
Missing6
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean137.5609756
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:12.609571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median104
Q3238
95-th percentile379
Maximum516
Range515
Interquartile range (IQR)217

Descriptive statistics

Standard deviation131.3684948
Coefficient of variation (CV)0.9549837387
Kurtosis0.3823801042
Mean137.5609756
Median Absolute Deviation (MAD)83
Skewness1.083545284
Sum11280
Variance17257.68142
MonotonicityNot monotonic
2022-09-05T21:40:12.710698image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2116
18.2%
10413
14.8%
2389
10.2%
16
 
6.8%
884
 
4.5%
3793
 
3.4%
3273
 
3.4%
1183
 
3.4%
302
 
2.3%
152
 
2.3%
Other values (17)21
23.9%
(Missing)6
 
6.8%
ValueCountFrequency (%)
16
 
6.8%
152
 
2.3%
201
 
1.1%
2116
18.2%
302
 
2.3%
512
 
2.3%
672
 
2.3%
831
 
1.1%
884
 
4.5%
991
 
1.1%
ValueCountFrequency (%)
5161
 
1.1%
5101
 
1.1%
4521
 
1.1%
3801
 
1.1%
3793
 
3.4%
3372
 
2.3%
3273
 
3.4%
3111
 
1.1%
2389
10.2%
2262
 
2.3%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct27
Distinct (%)32.9%
Missing6
Missing (%)6.8%
Memory size832.0 B
YouTube
16 
Tencent QQ
13 
NRK TV
Netflix
LINE TV
Other values (22)
34 

Length

Max length17
Median length12
Mean length7.792682927
Min length3

Characters and Unicode

Total characters639
Distinct characters48
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)15.9%

Sample

1st rowYouTube
2nd rowEpic Media
3rd rowivi
4th rowivi
5th rowSeezn

Common Values

ValueCountFrequency (%)
YouTube16
18.2%
Tencent QQ13
14.8%
NRK TV9
10.2%
Netflix6
 
6.8%
LINE TV4
 
4.5%
Shahid3
 
3.4%
TV 2 Play3
 
3.4%
Youku3
 
3.4%
Naver TVCast2
 
2.3%
WWE Network2
 
2.3%
Other values (17)21
23.9%
(Missing)6
 
6.8%

Length

2022-09-05T21:40:12.814677image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv18
14.6%
youtube16
13.0%
qq13
 
10.6%
tencent13
 
10.6%
nrk9
 
7.3%
netflix6
 
4.9%
line4
 
3.3%
shahid3
 
2.4%
23
 
2.4%
play3
 
2.4%
Other values (25)35
28.5%

Most occurring characters

ValueCountFrequency (%)
e65
 
10.2%
T50
 
7.8%
u45
 
7.0%
41
 
6.4%
n33
 
5.2%
o30
 
4.7%
t29
 
4.5%
i29
 
4.5%
Q28
 
4.4%
N24
 
3.8%
Other values (38)265
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter379
59.3%
Uppercase Letter213
33.3%
Space Separator41
 
6.4%
Decimal Number3
 
0.5%
Math Symbol2
 
0.3%
Other Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e65
17.2%
u45
11.9%
n33
8.7%
o30
7.9%
t29
 
7.7%
i29
 
7.7%
b21
 
5.5%
a19
 
5.0%
l18
 
4.7%
c16
 
4.2%
Other values (14)74
19.5%
Uppercase Letter
ValueCountFrequency (%)
T50
23.5%
Q28
13.1%
N24
11.3%
Y21
9.9%
V21
9.9%
R10
 
4.7%
K9
 
4.2%
I8
 
3.8%
E7
 
3.3%
W7
 
3.3%
Other values (10)28
13.1%
Space Separator
ValueCountFrequency (%)
41
100.0%
Decimal Number
ValueCountFrequency (%)
23
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin592
92.6%
Common47
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e65
 
11.0%
T50
 
8.4%
u45
 
7.6%
n33
 
5.6%
o30
 
5.1%
t29
 
4.9%
i29
 
4.9%
Q28
 
4.7%
N24
 
4.1%
Y21
 
3.5%
Other values (34)238
40.2%
Common
ValueCountFrequency (%)
41
87.2%
23
 
6.4%
+2
 
4.3%
.1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII639
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e65
 
10.2%
T50
 
7.8%
u45
 
7.0%
41
 
6.4%
n33
 
5.2%
o30
 
4.7%
t29
 
4.5%
i29
 
4.5%
Q28
 
4.4%
N24
 
3.8%
Other values (38)265
41.5%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)23.5%
Missing37
Missing (%)42.0%
Memory size832.0 B
https://www.youtube.com
16 
https://v.qq.com/
13 
https://www.netflix.com/
https://www.linetv.tw/
https://www.ivi.ru/
Other values (7)
10 

Length

Max length30
Median length24
Mean length21.39215686
Min length17

Characters and Unicode

Total characters1091
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)7.8%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://www.ivi.ru/
3rd rowhttps://www.ivi.ru/
4th rowhttps://www.seezntv.com/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com16
18.2%
https://v.qq.com/13
 
14.8%
https://www.netflix.com/6
 
6.8%
https://www.linetv.tw/4
 
4.5%
https://www.ivi.ru/2
 
2.3%
https://tv.naver.com/2
 
2.3%
https://w.mgtv.com/2
 
2.3%
https://www.iq.com/2
 
2.3%
https://www.seezntv.com/1
 
1.1%
http://www.wowpresentsplus.com1
 
1.1%
Other values (2)2
 
2.3%
(Missing)37
42.0%

Length

2022-09-05T21:40:12.906253image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com16
31.4%
https://v.qq.com13
25.5%
https://www.netflix.com6
 
11.8%
https://www.linetv.tw4
 
7.8%
https://www.ivi.ru2
 
3.9%
https://tv.naver.com2
 
3.9%
https://w.mgtv.com2
 
3.9%
https://www.iq.com2
 
3.9%
https://www.seezntv.com1
 
2.0%
http://www.wowpresentsplus.com1
 
2.0%
Other values (2)2
 
3.9%

Most occurring characters

ValueCountFrequency (%)
t139
12.7%
/136
12.5%
w110
 
10.1%
.102
 
9.3%
o64
 
5.9%
s57
 
5.2%
p56
 
5.1%
h51
 
4.7%
:51
 
4.7%
m48
 
4.4%
Other values (17)277
25.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter802
73.5%
Other Punctuation289
 
26.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t139
17.3%
w110
13.7%
o64
 
8.0%
s57
 
7.1%
p56
 
7.0%
h51
 
6.4%
m48
 
6.0%
c46
 
5.7%
u38
 
4.7%
e33
 
4.1%
Other values (14)160
20.0%
Other Punctuation
ValueCountFrequency (%)
/136
47.1%
.102
35.3%
:51
 
17.6%

Most occurring scripts

ValueCountFrequency (%)
Latin802
73.5%
Common289
 
26.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t139
17.3%
w110
13.7%
o64
 
8.0%
s57
 
7.1%
p56
 
7.0%
h51
 
6.4%
m48
 
6.0%
c46
 
5.7%
u38
 
4.7%
e33
 
4.1%
Other values (14)160
20.0%
Common
ValueCountFrequency (%)
/136
47.1%
.102
35.3%
:51
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1091
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t139
12.7%
/136
12.5%
w110
 
10.1%
.102
 
9.3%
o64
 
5.9%
s57
 
5.2%
p56
 
5.1%
h51
 
4.7%
:51
 
4.7%
m48
 
4.4%
Other values (17)277
25.4%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing86
Missing (%)97.7%
Memory size832.0 B
19056.0
25100.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row19056.0
2nd row25100.0

Common Values

ValueCountFrequency (%)
19056.01
 
1.1%
25100.01
 
1.1%
(Missing)86
97.7%

Length

2022-09-05T21:40:12.991771image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:13.077734image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
50.0%
25100.01
50.0%

Most occurring characters

ValueCountFrequency (%)
05
35.7%
12
 
14.3%
52
 
14.3%
.2
 
14.3%
91
 
7.1%
61
 
7.1%
21
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
85.7%
Other Punctuation2
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
41.7%
12
 
16.7%
52
 
16.7%
91
 
8.3%
61
 
8.3%
21
 
8.3%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
35.7%
12
 
14.3%
52
 
14.3%
.2
 
14.3%
91
 
7.1%
61
 
7.1%
21
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
35.7%
12
 
14.3%
52
 
14.3%
.2
 
14.3%
91
 
7.1%
61
 
7.1%
21
 
7.1%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)81.1%
Missing35
Missing (%)39.8%
Infinite0
Infinite (%)0.0%
Mean362493.0189
Minimum104271
Maximum410086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:13.163637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile278793
Q1369796
median380686
Q3392214
95-th percentile393454
Maximum410086
Range305815
Interquartile range (IQR)22418

Descriptive statistics

Standard deviation57197.07377
Coefficient of variation (CV)0.1577880698
Kurtosis10.7008181
Mean362493.0189
Median Absolute Deviation (MAD)11528
Skewness-3.085849299
Sum19212130
Variance3271505248
MonotonicityNot monotonic
2022-09-05T21:40:13.270280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
3921044
 
4.5%
3924102
 
2.3%
3922142
 
2.3%
3923622
 
2.3%
3926792
 
2.3%
2787932
 
2.3%
3921622
 
2.3%
3930602
 
2.3%
3710441
 
1.1%
3269621
 
1.1%
Other values (33)33
37.5%
(Missing)35
39.8%
ValueCountFrequency (%)
1042711
1.1%
1445411
1.1%
2787932
2.3%
2906861
1.1%
2941791
1.1%
3150611
1.1%
3213641
1.1%
3269621
1.1%
3366281
1.1%
3542161
1.1%
ValueCountFrequency (%)
4100861
1.1%
3952351
1.1%
3940451
1.1%
3930602
2.3%
3926821
1.1%
3926792
2.3%
3926491
1.1%
3924102
2.3%
3923622
2.3%
3922142
2.3%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct27
Distinct (%)69.2%
Missing49
Missing (%)55.7%
Memory size832.0 B
tt13650312
tt13487106
tt13470370
 
2
tt15561200
 
2
tt1714810
 
2
Other values (22)
24 

Length

Max length10
Median length10
Mean length9.692307692
Min length9

Characters and Unicode

Total characters378
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)51.3%

Sample

1st rowtt13695606
2nd rowtt10960302
3rd rowtt13470370
4th rowtt13470370
5th rowtt11492320

Common Values

ValueCountFrequency (%)
tt136503125
 
5.7%
tt134871064
 
4.5%
tt134703702
 
2.3%
tt155612002
 
2.3%
tt17148102
 
2.3%
tt135688762
 
2.3%
tt135397102
 
2.3%
tt66189221
 
1.1%
tt00965971
 
1.1%
tt96465461
 
1.1%
Other values (17)17
 
19.3%
(Missing)49
55.7%

Length

2022-09-05T21:40:13.370884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt136503125
 
12.8%
tt134871064
 
10.3%
tt134703702
 
5.1%
tt155612002
 
5.1%
tt17148102
 
5.1%
tt135688762
 
5.1%
tt135397102
 
5.1%
tt136956061
 
2.6%
tt109603021
 
2.6%
tt114923201
 
2.6%
Other values (17)17
43.6%

Most occurring characters

ValueCountFrequency (%)
t78
20.6%
155
14.6%
043
11.4%
639
10.3%
334
9.0%
224
 
6.3%
523
 
6.1%
822
 
5.8%
722
 
5.8%
421
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number300
79.4%
Lowercase Letter78
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
155
18.3%
043
14.3%
639
13.0%
334
11.3%
224
8.0%
523
7.7%
822
 
7.3%
722
 
7.3%
421
 
7.0%
917
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
t78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common300
79.4%
Latin78
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
155
18.3%
043
14.3%
639
13.0%
334
11.3%
224
8.0%
523
7.7%
822
 
7.3%
722
 
7.3%
421
 
7.0%
917
 
5.7%
Latin
ValueCountFrequency (%)
t78
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t78
20.6%
155
14.6%
043
11.4%
639
10.3%
334
9.0%
224
 
6.3%
523
 
6.1%
822
 
5.8%
722
 
5.8%
421
 
5.6%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct64
Distinct (%)75.3%
Missing3
Missing (%)3.4%
Memory size832.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/290/726864.jpg
 
5
https://static.tvmaze.com/uploads/images/medium_portrait/284/710019.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/226/565494.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/350/877137.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg
 
2
Other values (59)
68 

Length

Max length72
Median length71
Mean length71.04705882
Min length70

Characters and Unicode

Total characters6039
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)58.8%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/283/709704.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/726864.jpg5
 
5.7%
https://static.tvmaze.com/uploads/images/medium_portrait/284/710019.jpg4
 
4.5%
https://static.tvmaze.com/uploads/images/medium_portrait/226/565494.jpg4
 
4.5%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877137.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721821.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926884.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.3%
Other values (54)58
65.9%
(Missing)3
 
3.4%

Length

2022-09-05T21:40:13.471958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/726864.jpg5
 
5.9%
https://static.tvmaze.com/uploads/images/medium_portrait/226/565494.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/medium_portrait/284/710019.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926884.jpg2
 
2.4%
Other values (54)58
68.2%

Most occurring characters

ValueCountFrequency (%)
/595
 
9.9%
t595
 
9.9%
a425
 
7.0%
m425
 
7.0%
p340
 
5.6%
s340
 
5.6%
i340
 
5.6%
.255
 
4.2%
e255
 
4.2%
o255
 
4.2%
Other values (22)2214
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4250
70.4%
Other Punctuation935
 
15.5%
Decimal Number769
 
12.7%
Connector Punctuation85
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t595
14.0%
a425
10.0%
m425
10.0%
p340
 
8.0%
s340
 
8.0%
i340
 
8.0%
e255
 
6.0%
o255
 
6.0%
d170
 
4.0%
u170
 
4.0%
Other values (8)935
22.0%
Decimal Number
ValueCountFrequency (%)
2100
13.0%
788
11.4%
887
11.3%
186
11.2%
473
9.5%
071
9.2%
970
9.1%
670
9.1%
564
8.3%
360
7.8%
Other Punctuation
ValueCountFrequency (%)
/595
63.6%
.255
27.3%
:85
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4250
70.4%
Common1789
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t595
14.0%
a425
10.0%
m425
10.0%
p340
 
8.0%
s340
 
8.0%
i340
 
8.0%
e255
 
6.0%
o255
 
6.0%
d170
 
4.0%
u170
 
4.0%
Other values (8)935
22.0%
Common
ValueCountFrequency (%)
/595
33.3%
.255
14.3%
2100
 
5.6%
788
 
4.9%
887
 
4.9%
186
 
4.8%
_85
 
4.8%
:85
 
4.8%
473
 
4.1%
071
 
4.0%
Other values (4)264
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/595
 
9.9%
t595
 
9.9%
a425
 
7.0%
m425
 
7.0%
p340
 
5.6%
s340
 
5.6%
i340
 
5.6%
.255
 
4.2%
e255
 
4.2%
o255
 
4.2%
Other values (22)2214
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct64
Distinct (%)75.3%
Missing3
Missing (%)3.4%
Memory size832.0 B
https://static.tvmaze.com/uploads/images/original_untouched/290/726864.jpg
 
5
https://static.tvmaze.com/uploads/images/original_untouched/284/710019.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/226/565494.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/350/877137.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg
 
2
Other values (59)
68 

Length

Max length75
Median length74
Mean length74.04705882
Min length73

Characters and Unicode

Total characters6294
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)58.8%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/283/709704.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726864.jpg5
 
5.7%
https://static.tvmaze.com/uploads/images/original_untouched/284/710019.jpg4
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/226/565494.jpg4
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/350/877137.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/288/721821.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/370/926884.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.3%
Other values (54)58
65.9%
(Missing)3
 
3.4%

Length

2022-09-05T21:40:13.580664image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726864.jpg5
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/226/565494.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/original_untouched/284/710019.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/370/926884.jpg2
 
2.4%
Other values (54)58
68.2%

Most occurring characters

ValueCountFrequency (%)
/595
 
9.5%
t510
 
8.1%
a425
 
6.8%
s340
 
5.4%
i340
 
5.4%
o340
 
5.4%
p255
 
4.1%
c255
 
4.1%
.255
 
4.1%
g255
 
4.1%
Other values (23)2724
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4505
71.6%
Other Punctuation935
 
14.9%
Decimal Number769
 
12.2%
Connector Punctuation85
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t510
 
11.3%
a425
 
9.4%
s340
 
7.5%
i340
 
7.5%
o340
 
7.5%
p255
 
5.7%
c255
 
5.7%
g255
 
5.7%
m255
 
5.7%
e255
 
5.7%
Other values (9)1275
28.3%
Decimal Number
ValueCountFrequency (%)
2100
13.0%
788
11.4%
887
11.3%
186
11.2%
473
9.5%
071
9.2%
970
9.1%
670
9.1%
564
8.3%
360
7.8%
Other Punctuation
ValueCountFrequency (%)
/595
63.6%
.255
27.3%
:85
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4505
71.6%
Common1789
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t510
 
11.3%
a425
 
9.4%
s340
 
7.5%
i340
 
7.5%
o340
 
7.5%
p255
 
5.7%
c255
 
5.7%
g255
 
5.7%
m255
 
5.7%
e255
 
5.7%
Other values (9)1275
28.3%
Common
ValueCountFrequency (%)
/595
33.3%
.255
14.3%
2100
 
5.6%
788
 
4.9%
887
 
4.9%
186
 
4.8%
:85
 
4.8%
_85
 
4.8%
473
 
4.1%
071
 
4.0%
Other values (4)264
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6294
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/595
 
9.5%
t510
 
8.1%
a425
 
6.8%
s340
 
5.4%
i340
 
5.4%
o340
 
5.4%
p255
 
4.1%
c255
 
4.1%
.255
 
4.1%
g255
 
4.1%
Other values (23)2724
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct55
Distinct (%)72.4%
Missing12
Missing (%)13.6%
Memory size832.0 B
<p>Can a dab of vodka, a little rølp and a good dose of amateur hockey break down barriers and create friendships? The happy hockey amateurs in <b>Kirkenes Puckers</b> think so.</p>
 
5
<p><b>The Surgeon's Cut </b>profiles four ground-breaking surgeons from around the world, each with a visionary approach to their craft. Viewers will follow along as they perform innovative operations and procedures, and reveal personal insight into their journey into medicine, providing a unique window into the world of surgery. Through the individual stories of these experts, the series explores how our understanding of the human body is constantly being reinvented by new discoveries and techniques. Specialty areas featured include fetal medicine, neurosurgery, transplant surgery and cardiology. </p>
 
4
<p>Jump aboard with Robbie Cumming as he embarks on a 300-mile journey across the Midlands and northern England in his narrowboat.</p>
 
4
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>
 
2
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>
 
2
Other values (50)
59 

Length

Max length807
Median length363
Mean length305.3421053
Min length36

Characters and Unicode

Total characters23206
Distinct characters89
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)53.9%

Sample

1st row<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>
2nd row<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>
3rd row<p><b>Mermaid Prince</b> is about Hye Ri, who embarks on a graduation trip to Gangwon Province and meets Woo Hyuk, a mysterious guy who runs a guest house.</p>
4th row<p>The pure and cute little devil Nini lives in Room 1031 of Wan Sheng Street Apartment. His roommates are no ordinary people: The lazy and wacky vampire Ira who spends most of his time gaming or watching TV, the unlucky dancer werewolf Vladimir, the serious and old-fashioned angel landlord Lynn and his naive little sister Lily, and many more.<br /><br />What none of them realize is that the power of the demon king is sleeping inside of Nini. With evil forces in hot pursuit, can Nini and his friends head off disaster?</p>
5th row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>

Common Values

ValueCountFrequency (%)
<p>Can a dab of vodka, a little rølp and a good dose of amateur hockey break down barriers and create friendships? The happy hockey amateurs in <b>Kirkenes Puckers</b> think so.</p>5
 
5.7%
<p><b>The Surgeon's Cut </b>profiles four ground-breaking surgeons from around the world, each with a visionary approach to their craft. Viewers will follow along as they perform innovative operations and procedures, and reveal personal insight into their journey into medicine, providing a unique window into the world of surgery. Through the individual stories of these experts, the series explores how our understanding of the human body is constantly being reinvented by new discoveries and techniques. Specialty areas featured include fetal medicine, neurosurgery, transplant surgery and cardiology. </p>4
 
4.5%
<p>Jump aboard with Robbie Cumming as he embarks on a 300-mile journey across the Midlands and northern England in his narrowboat.</p>4
 
4.5%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>2
 
2.3%
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>2
 
2.3%
<p>‎Shen Moo, has no idea what adventures she will face. Beauty, is one of the best observers of Internet resources, but soon, in her head creeps the idea that in the universe there are mermaids. It's hard to believe, but for some reason, she can't get it out of her mind. Soon, she will have to take responsibility to prove their existence, otherwise, the dispute with the professor will turn out to be a real failure for the heroine. Together with the rescue team, they went to help the victims in The Xine Bay. Meet Ahn Xin - an athlete, will turn her reality. Unbelievable, but the guy is perceived as a mermaid. Of course, Mu Xin liked it madly, because she found a key witness and will be able to insist on her own. However, the mermaid man does his best to avoid revealing his real world.‎</p>2
 
2.3%
<p>A story that follows a detective in the major crimes division of Nan Xing City Police Department. Together with a woman who has super memory, he upholds the law one case at a time in solving murders, burglaries and bringing down a narcotics manufacturing facility. Jing Chu is a young and capable detective. Due to his repeated merits from cracking big cases, he is promoted to the position of major crimes division vice-captain at Nan Xing city and starts to work alongside his new team. Because of a murder case, he meets Yang Mian Mian, a young woman who possesses a photographic memory. He soon realizes that Mian Mian seems to have a deep connection to his father's mysterious death many years ago. Meanwhile, a famous blogger and a member of an idol girl group die</p>2
 
2.3%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
2.3%
<p>Morten shows you how you can make something cool with what you have at home!</p>2
 
2.3%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
2.3%
Other values (45)49
55.7%
(Missing)12
 
13.6%

Length

2022-09-05T21:40:13.717607image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the175
 
4.6%
and145
 
3.8%
a134
 
3.5%
to112
 
2.9%
of97
 
2.5%
in70
 
1.8%
his54
 
1.4%
with52
 
1.4%
he35
 
0.9%
is30
 
0.8%
Other values (1239)2932
76.4%

Most occurring characters

ValueCountFrequency (%)
3754
16.2%
e2144
 
9.2%
a1452
 
6.3%
n1393
 
6.0%
t1347
 
5.8%
o1340
 
5.8%
i1329
 
5.7%
s1127
 
4.9%
r1099
 
4.7%
h872
 
3.8%
Other values (79)7349
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17556
75.7%
Space Separator3761
 
16.2%
Uppercase Letter717
 
3.1%
Other Punctuation615
 
2.7%
Math Symbol428
 
1.8%
Dash Punctuation54
 
0.2%
Decimal Number44
 
0.2%
Format16
 
0.1%
Open Punctuation6
 
< 0.1%
Close Punctuation6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2144
12.2%
a1452
 
8.3%
n1393
 
7.9%
t1347
 
7.7%
o1340
 
7.6%
i1329
 
7.6%
s1127
 
6.4%
r1099
 
6.3%
h872
 
5.0%
l699
 
4.0%
Other values (20)4754
27.1%
Uppercase Letter
ValueCountFrequency (%)
S75
 
10.5%
T56
 
7.8%
M48
 
6.7%
H42
 
5.9%
W41
 
5.7%
A38
 
5.3%
C37
 
5.2%
B34
 
4.7%
Y30
 
4.2%
X28
 
3.9%
Other values (16)288
40.2%
Other Punctuation
ValueCountFrequency (%)
,211
34.3%
.198
32.2%
/117
19.0%
'42
 
6.8%
"20
 
3.3%
?13
 
2.1%
!5
 
0.8%
:4
 
0.7%
;1
 
0.2%
&1
 
0.2%
Other values (3)3
 
0.5%
Decimal Number
ValueCountFrequency (%)
021
47.7%
26
 
13.6%
35
 
11.4%
15
 
11.4%
83
 
6.8%
72
 
4.5%
51
 
2.3%
41
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-51
94.4%
2
 
3.7%
1
 
1.9%
Space Separator
ValueCountFrequency (%)
3754
99.8%
 7
 
0.2%
Math Symbol
ValueCountFrequency (%)
>214
50.0%
<214
50.0%
Currency Symbol
ValueCountFrequency (%)
$2
66.7%
1
33.3%
Format
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
(6
100.0%
Close Punctuation
ValueCountFrequency (%)
)6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin18273
78.7%
Common4933
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2144
 
11.7%
a1452
 
7.9%
n1393
 
7.6%
t1347
 
7.4%
o1340
 
7.3%
i1329
 
7.3%
s1127
 
6.2%
r1099
 
6.0%
h872
 
4.8%
l699
 
3.8%
Other values (46)5471
29.9%
Common
ValueCountFrequency (%)
3754
76.1%
>214
 
4.3%
<214
 
4.3%
,211
 
4.3%
.198
 
4.0%
/117
 
2.4%
-51
 
1.0%
'42
 
0.9%
021
 
0.4%
"20
 
0.4%
Other values (23)91
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII23170
99.8%
Punctuation20
 
0.1%
None15
 
0.1%
Currency Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3754
16.2%
e2144
 
9.3%
a1452
 
6.3%
n1393
 
6.0%
t1347
 
5.8%
o1340
 
5.8%
i1329
 
5.7%
s1127
 
4.9%
r1099
 
4.7%
h872
 
3.8%
Other values (69)7313
31.6%
Punctuation
ValueCountFrequency (%)
16
80.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
None
ValueCountFrequency (%)
 7
46.7%
ø5
33.3%
æ1
 
6.7%
é1
 
6.7%
å1
 
6.7%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct67
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1638747132
Minimum1607548768
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:13.846519image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1607548768
5-th percentile1609006074
Q11613087921
median1646937966
Q31656819246
95-th percentile1662277835
Maximum1662346277
Range54797509
Interquartile range (IQR)43731324.75

Descriptive statistics

Standard deviation20464388.55
Coefficient of variation (CV)0.0124878257
Kurtosis-1.500362898
Mean1638747132
Median Absolute Deviation (MAD)14741179
Skewness-0.3923952568
Sum1.442097476 × 1011
Variance4.187911988 × 1014
MonotonicityNot monotonic
2022-09-05T21:40:13.973909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16090060745
 
5.7%
16622790024
 
4.5%
16497929814
 
4.5%
16508264802
 
2.3%
16357351792
 
2.3%
16481900582
 
2.3%
16549774442
 
2.3%
16196334992
 
2.3%
16128425832
 
2.3%
16090607262
 
2.3%
Other values (57)61
69.3%
ValueCountFrequency (%)
16075487681
 
1.1%
16082530132
 
2.3%
16090060745
5.7%
16090607262
 
2.3%
16095351412
 
2.3%
16102051551
 
1.1%
16108125261
 
1.1%
16108903401
 
1.1%
16114368421
 
1.1%
16120078311
 
1.1%
ValueCountFrequency (%)
16623462771
 
1.1%
16622790024
4.5%
16622756681
 
1.1%
16622179311
 
1.1%
16622069171
 
1.1%
16620501331
 
1.1%
16619691591
 
1.1%
16619595381
 
1.1%
16619226521
 
1.1%
16618725611
 
1.1%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct67
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size832.0 B
https://api.tvmaze.com/shows/52639
 
5
https://api.tvmaze.com/shows/45155
 
4
https://api.tvmaze.com/shows/51992
 
4
https://api.tvmaze.com/shows/52108
 
2
https://api.tvmaze.com/shows/58689
 
2
Other values (62)
71 

Length

Max length34
Median length34
Mean length33.97727273
Min length33

Characters and Unicode

Total characters2990
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)60.2%

Sample

1st rowhttps://api.tvmaze.com/shows/49630
2nd rowhttps://api.tvmaze.com/shows/52198
3rd rowhttps://api.tvmaze.com/shows/52316
4th rowhttps://api.tvmaze.com/shows/52316
5th rowhttps://api.tvmaze.com/shows/47207

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/526395
 
5.7%
https://api.tvmaze.com/shows/451554
 
4.5%
https://api.tvmaze.com/shows/519924
 
4.5%
https://api.tvmaze.com/shows/521082
 
2.3%
https://api.tvmaze.com/shows/586892
 
2.3%
https://api.tvmaze.com/shows/152502
 
2.3%
https://api.tvmaze.com/shows/527802
 
2.3%
https://api.tvmaze.com/shows/524212
 
2.3%
https://api.tvmaze.com/shows/524002
 
2.3%
https://api.tvmaze.com/shows/521592
 
2.3%
Other values (57)61
69.3%

Length

2022-09-05T21:40:14.066419image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/526395
 
5.7%
https://api.tvmaze.com/shows/519924
 
4.5%
https://api.tvmaze.com/shows/451554
 
4.5%
https://api.tvmaze.com/shows/524002
 
2.3%
https://api.tvmaze.com/shows/521042
 
2.3%
https://api.tvmaze.com/shows/521072
 
2.3%
https://api.tvmaze.com/shows/570302
 
2.3%
https://api.tvmaze.com/shows/521592
 
2.3%
https://api.tvmaze.com/shows/523162
 
2.3%
https://api.tvmaze.com/shows/524212
 
2.3%
Other values (57)61
69.3%

Most occurring characters

ValueCountFrequency (%)
/352
 
11.8%
s264
 
8.8%
t264
 
8.8%
h176
 
5.9%
p176
 
5.9%
a176
 
5.9%
o176
 
5.9%
.176
 
5.9%
m176
 
5.9%
e88
 
2.9%
Other values (16)966
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1936
64.7%
Other Punctuation616
 
20.6%
Decimal Number438
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s264
13.6%
t264
13.6%
h176
9.1%
p176
9.1%
a176
9.1%
o176
9.1%
m176
9.1%
e88
 
4.5%
w88
 
4.5%
c88
 
4.5%
Other values (3)264
13.6%
Decimal Number
ValueCountFrequency (%)
587
19.9%
252
11.9%
451
11.6%
141
9.4%
939
8.9%
038
8.7%
336
8.2%
634
 
7.8%
733
 
7.5%
827
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/352
57.1%
.176
28.6%
:88
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1936
64.7%
Common1054
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/352
33.4%
.176
16.7%
:88
 
8.3%
587
 
8.3%
252
 
4.9%
451
 
4.8%
141
 
3.9%
939
 
3.7%
038
 
3.6%
336
 
3.4%
Other values (3)94
 
8.9%
Latin
ValueCountFrequency (%)
s264
13.6%
t264
13.6%
h176
9.1%
p176
9.1%
a176
9.1%
o176
9.1%
m176
9.1%
e88
 
4.5%
w88
 
4.5%
c88
 
4.5%
Other values (3)264
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/352
 
11.8%
s264
 
8.8%
t264
 
8.8%
h176
 
5.9%
p176
 
5.9%
a176
 
5.9%
o176
 
5.9%
.176
 
5.9%
m176
 
5.9%
e88
 
2.9%
Other values (16)966
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct67
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size832.0 B
https://api.tvmaze.com/episodes/1993071
 
5
https://api.tvmaze.com/episodes/2293679
 
4
https://api.tvmaze.com/episodes/1972645
 
4
https://api.tvmaze.com/episodes/1976202
 
2
https://api.tvmaze.com/episodes/2205983
 
2
Other values (62)
71 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3432
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)60.2%

Sample

1st rowhttps://api.tvmaze.com/episodes/2380515
2nd rowhttps://api.tvmaze.com/episodes/1986873
3rd rowhttps://api.tvmaze.com/episodes/1983260
4th rowhttps://api.tvmaze.com/episodes/1983260
5th rowhttps://api.tvmaze.com/episodes/1971570

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19930715
 
5.7%
https://api.tvmaze.com/episodes/22936794
 
4.5%
https://api.tvmaze.com/episodes/19726454
 
4.5%
https://api.tvmaze.com/episodes/19762022
 
2.3%
https://api.tvmaze.com/episodes/22059832
 
2.3%
https://api.tvmaze.com/episodes/23012762
 
2.3%
https://api.tvmaze.com/episodes/19985382
 
2.3%
https://api.tvmaze.com/episodes/19854962
 
2.3%
https://api.tvmaze.com/episodes/19849632
 
2.3%
https://api.tvmaze.com/episodes/19776512
 
2.3%
Other values (57)61
69.3%

Length

2022-09-05T21:40:14.143131image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19930715
 
5.7%
https://api.tvmaze.com/episodes/19726454
 
4.5%
https://api.tvmaze.com/episodes/22936794
 
4.5%
https://api.tvmaze.com/episodes/19849632
 
2.3%
https://api.tvmaze.com/episodes/19760542
 
2.3%
https://api.tvmaze.com/episodes/19761662
 
2.3%
https://api.tvmaze.com/episodes/21701272
 
2.3%
https://api.tvmaze.com/episodes/19776512
 
2.3%
https://api.tvmaze.com/episodes/19832602
 
2.3%
https://api.tvmaze.com/episodes/19854962
 
2.3%
Other values (57)61
69.3%

Most occurring characters

ValueCountFrequency (%)
/352
 
10.3%
t264
 
7.7%
p264
 
7.7%
s264
 
7.7%
e264
 
7.7%
a176
 
5.1%
i176
 
5.1%
.176
 
5.1%
m176
 
5.1%
o176
 
5.1%
Other values (16)1144
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2200
64.1%
Other Punctuation616
 
17.9%
Decimal Number616
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t264
12.0%
p264
12.0%
s264
12.0%
e264
12.0%
a176
8.0%
i176
8.0%
m176
8.0%
o176
8.0%
h88
 
4.0%
d88
 
4.0%
Other values (3)264
12.0%
Decimal Number
ValueCountFrequency (%)
2110
17.9%
980
13.0%
179
12.8%
761
9.9%
358
9.4%
654
8.8%
050
8.1%
547
7.6%
844
 
7.1%
433
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/352
57.1%
.176
28.6%
:88
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2200
64.1%
Common1232
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/352
28.6%
.176
14.3%
2110
 
8.9%
:88
 
7.1%
980
 
6.5%
179
 
6.4%
761
 
5.0%
358
 
4.7%
654
 
4.4%
050
 
4.1%
Other values (3)124
 
10.1%
Latin
ValueCountFrequency (%)
t264
12.0%
p264
12.0%
s264
12.0%
e264
12.0%
a176
8.0%
i176
8.0%
m176
8.0%
o176
8.0%
h88
 
4.0%
d88
 
4.0%
Other values (3)264
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/352
 
10.3%
t264
 
7.7%
p264
 
7.7%
s264
 
7.7%
e264
 
7.7%
a176
 
5.1%
i176
 
5.1%
.176
 
5.1%
m176
 
5.1%
o176
 
5.1%
Other values (16)1144
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)15.6%
Missing43
Missing (%)48.9%
Memory size832.0 B
China
20 
Norway
12 
Russian Federation
United States
Korea, Republic of
Other values (2)
 
2

Length

Max length18
Median length13
Mean length8.133333333
Min length5

Characters and Unicode

Total characters366
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.4%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowKorea, Republic of
5th rowChina

Common Values

ValueCountFrequency (%)
China20
22.7%
Norway12
 
13.6%
Russian Federation4
 
4.5%
United States4
 
4.5%
Korea, Republic of3
 
3.4%
Kazakhstan1
 
1.1%
Brazil1
 
1.1%
(Missing)43
48.9%

Length

2022-09-05T21:40:14.225470image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:14.328068image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china20
33.9%
norway12
20.3%
russian4
 
6.8%
federation4
 
6.8%
united4
 
6.8%
states4
 
6.8%
korea3
 
5.1%
republic3
 
5.1%
of3
 
5.1%
kazakhstan1
 
1.7%

Most occurring characters

ValueCountFrequency (%)
a51
13.9%
i36
 
9.8%
n33
 
9.0%
e22
 
6.0%
o22
 
6.0%
h21
 
5.7%
r20
 
5.5%
C20
 
5.5%
t17
 
4.6%
14
 
3.8%
Other values (20)110
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter293
80.1%
Uppercase Letter56
 
15.3%
Space Separator14
 
3.8%
Other Punctuation3
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a51
17.4%
i36
12.3%
n33
11.3%
e22
7.5%
o22
7.5%
h21
7.2%
r20
 
6.8%
t17
 
5.8%
s13
 
4.4%
w12
 
4.1%
Other values (10)46
15.7%
Uppercase Letter
ValueCountFrequency (%)
C20
35.7%
N12
21.4%
R7
 
12.5%
K4
 
7.1%
S4
 
7.1%
U4
 
7.1%
F4
 
7.1%
B1
 
1.8%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin349
95.4%
Common17
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a51
14.6%
i36
 
10.3%
n33
 
9.5%
e22
 
6.3%
o22
 
6.3%
h21
 
6.0%
r20
 
5.7%
C20
 
5.7%
t17
 
4.9%
s13
 
3.7%
Other values (18)94
26.9%
Common
ValueCountFrequency (%)
14
82.4%
,3
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a51
13.9%
i36
 
9.8%
n33
 
9.0%
e22
 
6.0%
o22
 
6.0%
h21
 
5.7%
r20
 
5.5%
C20
 
5.5%
t17
 
4.6%
14
 
3.8%
Other values (20)110
30.1%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)15.6%
Missing43
Missing (%)48.9%
Memory size832.0 B
CN
20 
NO
12 
RU
US
KR
Other values (2)
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters90
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.4%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowKR
5th rowCN

Common Values

ValueCountFrequency (%)
CN20
22.7%
NO12
 
13.6%
RU4
 
4.5%
US4
 
4.5%
KR3
 
3.4%
KZ1
 
1.1%
BR1
 
1.1%
(Missing)43
48.9%

Length

2022-09-05T21:40:14.419432image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:14.528662image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn20
44.4%
no12
26.7%
ru4
 
8.9%
us4
 
8.9%
kr3
 
6.7%
kz1
 
2.2%
br1
 
2.2%

Most occurring characters

ValueCountFrequency (%)
N32
35.6%
C20
22.2%
O12
 
13.3%
R8
 
8.9%
U8
 
8.9%
S4
 
4.4%
K4
 
4.4%
Z1
 
1.1%
B1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter90
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N32
35.6%
C20
22.2%
O12
 
13.3%
R8
 
8.9%
U8
 
8.9%
S4
 
4.4%
K4
 
4.4%
Z1
 
1.1%
B1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin90
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N32
35.6%
C20
22.2%
O12
 
13.3%
R8
 
8.9%
U8
 
8.9%
S4
 
4.4%
K4
 
4.4%
Z1
 
1.1%
B1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N32
35.6%
C20
22.2%
O12
 
13.3%
R8
 
8.9%
U8
 
8.9%
S4
 
4.4%
K4
 
4.4%
Z1
 
1.1%
B1
 
1.1%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)15.6%
Missing43
Missing (%)48.9%
Memory size832.0 B
Asia/Shanghai
20 
Europe/Oslo
12 
Asia/Kamchatka
America/New_York
Asia/Seoul
Other values (2)
 
2

Length

Max length16
Median length15
Mean length12.68888889
Min length10

Characters and Unicode

Total characters571
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.4%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Seoul
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai20
22.7%
Europe/Oslo12
 
13.6%
Asia/Kamchatka4
 
4.5%
America/New_York4
 
4.5%
Asia/Seoul3
 
3.4%
Asia/Qyzylorda1
 
1.1%
America/Noronha1
 
1.1%
(Missing)43
48.9%

Length

2022-09-05T21:40:14.630132image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:14.747722image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai20
44.4%
europe/oslo12
26.7%
asia/kamchatka4
 
8.9%
america/new_york4
 
8.9%
asia/seoul3
 
6.7%
asia/qyzylorda1
 
2.2%
america/noronha1
 
2.2%

Most occurring characters

ValueCountFrequency (%)
a87
15.2%
i53
 
9.3%
/45
 
7.9%
h45
 
7.9%
s40
 
7.0%
o34
 
6.0%
A33
 
5.8%
e24
 
4.2%
S23
 
4.0%
r23
 
4.0%
Other values (20)164
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter428
75.0%
Uppercase Letter94
 
16.5%
Other Punctuation45
 
7.9%
Connector Punctuation4
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a87
20.3%
i53
12.4%
h45
10.5%
s40
9.3%
o34
 
7.9%
e24
 
5.6%
r23
 
5.4%
n21
 
4.9%
g20
 
4.7%
l16
 
3.7%
Other values (10)65
15.2%
Uppercase Letter
ValueCountFrequency (%)
A33
35.1%
S23
24.5%
O12
 
12.8%
E12
 
12.8%
N5
 
5.3%
K4
 
4.3%
Y4
 
4.3%
Q1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/45
100.0%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin522
91.4%
Common49
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a87
16.7%
i53
 
10.2%
h45
 
8.6%
s40
 
7.7%
o34
 
6.5%
A33
 
6.3%
e24
 
4.6%
S23
 
4.4%
r23
 
4.4%
n21
 
4.0%
Other values (18)139
26.6%
Common
ValueCountFrequency (%)
/45
91.8%
_4
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a87
15.2%
i53
 
9.3%
/45
 
7.9%
h45
 
7.9%
s40
 
7.0%
o34
 
6.0%
A33
 
5.8%
e24
 
4.2%
S23
 
4.0%
r23
 
4.0%
Other values (20)164
28.7%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing81
Missing (%)92.0%
Memory size832.0 B
https://api.tvmaze.com/episodes/2374449
https://api.tvmaze.com/episodes/2373586
https://api.tvmaze.com/episodes/2382856
https://api.tvmaze.com/episodes/2383014
https://api.tvmaze.com/episodes/2371586
Other values (2)

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters273
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2374449
2nd rowhttps://api.tvmaze.com/episodes/2373586
3rd rowhttps://api.tvmaze.com/episodes/2382856
4th rowhttps://api.tvmaze.com/episodes/2383014
5th rowhttps://api.tvmaze.com/episodes/2371586

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
 
1.1%
https://api.tvmaze.com/episodes/23735861
 
1.1%
https://api.tvmaze.com/episodes/23828561
 
1.1%
https://api.tvmaze.com/episodes/23830141
 
1.1%
https://api.tvmaze.com/episodes/23715861
 
1.1%
https://api.tvmaze.com/episodes/23797031
 
1.1%
https://api.tvmaze.com/episodes/23671071
 
1.1%
(Missing)81
92.0%

Length

2022-09-05T21:40:14.845477image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:14.948305image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
14.3%
https://api.tvmaze.com/episodes/23735861
14.3%
https://api.tvmaze.com/episodes/23828561
14.3%
https://api.tvmaze.com/episodes/23830141
14.3%
https://api.tvmaze.com/episodes/23715861
14.3%
https://api.tvmaze.com/episodes/23797031
14.3%
https://api.tvmaze.com/episodes/23671071
14.3%

Most occurring characters

ValueCountFrequency (%)
/28
 
10.3%
p21
 
7.7%
s21
 
7.7%
e21
 
7.7%
t21
 
7.7%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
o14
 
5.1%
Other values (16)91
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter175
64.1%
Other Punctuation49
 
17.9%
Decimal Number49
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p21
12.0%
s21
12.0%
e21
12.0%
t21
12.0%
a14
8.0%
i14
8.0%
m14
8.0%
o14
8.0%
h7
 
4.0%
d7
 
4.0%
Other values (3)21
12.0%
Decimal Number
ValueCountFrequency (%)
310
20.4%
28
16.3%
77
14.3%
85
10.2%
44
 
8.2%
64
 
8.2%
53
 
6.1%
03
 
6.1%
13
 
6.1%
92
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/28
57.1%
.14
28.6%
:7
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin175
64.1%
Common98
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/28
28.6%
.14
14.3%
310
 
10.2%
28
 
8.2%
77
 
7.1%
:7
 
7.1%
85
 
5.1%
44
 
4.1%
64
 
4.1%
53
 
3.1%
Other values (3)8
 
8.2%
Latin
ValueCountFrequency (%)
p21
12.0%
s21
12.0%
e21
12.0%
t21
12.0%
a14
8.0%
i14
8.0%
m14
8.0%
o14
8.0%
h7
 
4.0%
d7
 
4.0%
Other values (3)21
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/28
 
10.3%
p21
 
7.7%
s21
 
7.7%
e21
 
7.7%
t21
 
7.7%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
o14
 
5.1%
Other values (16)91
33.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)76.9%
Missing75
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean519.8461538
Minimum30
Maximum1862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size832.0 B
2022-09-05T21:40:15.037380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile42.6
Q151
median132
Q3514
95-th percentile1829.6
Maximum1862
Range1832
Interquartile range (IQR)463

Descriptive statistics

Standard deviation681.4283829
Coefficient of variation (CV)1.310827017
Kurtosis0.3635859858
Mean519.8461538
Median Absolute Deviation (MAD)102
Skewness1.371616396
Sum6758
Variance464344.641
MonotonicityNot monotonic
2022-09-05T21:40:15.118656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
514
 
4.5%
5141
 
1.1%
18081
 
1.1%
18621
 
1.1%
3741
 
1.1%
4021
 
1.1%
13201
 
1.1%
1121
 
1.1%
301
 
1.1%
1321
 
1.1%
(Missing)75
85.2%
ValueCountFrequency (%)
301
 
1.1%
514
4.5%
1121
 
1.1%
1321
 
1.1%
3741
 
1.1%
4021
 
1.1%
5141
 
1.1%
13201
 
1.1%
18081
 
1.1%
18621
 
1.1%
ValueCountFrequency (%)
18621
 
1.1%
18081
 
1.1%
13201
 
1.1%
5141
 
1.1%
4021
 
1.1%
3741
 
1.1%
1321
 
1.1%
1121
 
1.1%
514
4.5%
301
 
1.1%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)76.9%
Missing75
Missing (%)85.2%
Memory size832.0 B
BBC Four
ТВ-3
MBC Masr
AfricaMagic Showcase
TV Globo
Other values (5)

Length

Max length20
Median length8
Mean length8.846153846
Min length4

Characters and Unicode

Total characters115
Distinct characters51
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)69.2%

Sample

1st rowТВ-3
2nd rowMBC Masr
3rd rowAfricaMagic Showcase
4th rowTV Globo
5th rowНовий Канал

Common Values

ValueCountFrequency (%)
BBC Four4
 
4.5%
ТВ-31
 
1.1%
MBC Masr1
 
1.1%
AfricaMagic Showcase1
 
1.1%
TV Globo1
 
1.1%
Новий Канал1
 
1.1%
UA:Перший1
 
1.1%
RTL41
 
1.1%
USA Network1
 
1.1%
Tokyo MX1
 
1.1%
(Missing)75
85.2%

Length

2022-09-05T21:40:15.213659image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:15.332463image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
bbc4
17.4%
four4
17.4%
новий1
 
4.3%
tokyo1
 
4.3%
network1
 
4.3%
usa1
 
4.3%
rtl41
 
4.3%
ua:перший1
 
4.3%
канал1
 
4.3%
globo1
 
4.3%
Other values (7)7
30.4%

Most occurring characters

ValueCountFrequency (%)
10
 
8.7%
o10
 
8.7%
B9
 
7.8%
r7
 
6.1%
C5
 
4.3%
M4
 
3.5%
F4
 
3.5%
u4
 
3.5%
a4
 
3.5%
T3
 
2.6%
Other values (41)55
47.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter58
50.4%
Uppercase Letter43
37.4%
Space Separator10
 
8.7%
Decimal Number2
 
1.7%
Other Punctuation1
 
0.9%
Dash Punctuation1
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o10
17.2%
r7
 
12.1%
u4
 
6.9%
a4
 
6.9%
c3
 
5.2%
k2
 
3.4%
w2
 
3.4%
й2
 
3.4%
и2
 
3.4%
s2
 
3.4%
Other values (17)20
34.5%
Uppercase Letter
ValueCountFrequency (%)
B9
20.9%
C5
11.6%
M4
9.3%
F4
9.3%
T3
 
7.0%
A3
 
7.0%
U2
 
4.7%
S2
 
4.7%
R1
 
2.3%
L1
 
2.3%
Other values (9)9
20.9%
Decimal Number
ValueCountFrequency (%)
41
50.0%
31
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
:1
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin83
72.2%
Cyrillic18
 
15.7%
Common14
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o10
 
12.0%
B9
 
10.8%
r7
 
8.4%
C5
 
6.0%
M4
 
4.8%
F4
 
4.8%
u4
 
4.8%
a4
 
4.8%
T3
 
3.6%
A3
 
3.6%
Other values (21)30
36.1%
Cyrillic
ValueCountFrequency (%)
й2
 
11.1%
и2
 
11.1%
а2
 
11.1%
н1
 
5.6%
ш1
 
5.6%
р1
 
5.6%
е1
 
5.6%
П1
 
5.6%
л1
 
5.6%
К1
 
5.6%
Other values (5)5
27.8%
Common
ValueCountFrequency (%)
10
71.4%
:1
 
7.1%
41
 
7.1%
31
 
7.1%
-1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII97
84.3%
Cyrillic18
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
 
10.3%
o10
 
10.3%
B9
 
9.3%
r7
 
7.2%
C5
 
5.2%
M4
 
4.1%
F4
 
4.1%
u4
 
4.1%
a4
 
4.1%
T3
 
3.1%
Other values (26)37
38.1%
Cyrillic
ValueCountFrequency (%)
й2
 
11.1%
и2
 
11.1%
а2
 
11.1%
н1
 
5.6%
ш1
 
5.6%
р1
 
5.6%
е1
 
5.6%
П1
 
5.6%
л1
 
5.6%
К1
 
5.6%
Other values (5)5
27.8%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)69.2%
Missing75
Missing (%)85.2%
Memory size832.0 B
United Kingdom
Ukraine
Russian Federation
Egypt
South Africa
Other values (4)

Length

Max length18
Median length13
Mean length10.76923077
Min length5

Characters and Unicode

Total characters140
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)53.8%

Sample

1st rowRussian Federation
2nd rowEgypt
3rd rowSouth Africa
4th rowBrazil
5th rowUkraine

Common Values

ValueCountFrequency (%)
United Kingdom4
 
4.5%
Ukraine2
 
2.3%
Russian Federation1
 
1.1%
Egypt1
 
1.1%
South Africa1
 
1.1%
Brazil1
 
1.1%
Netherlands1
 
1.1%
United States1
 
1.1%
Japan1
 
1.1%
(Missing)75
85.2%

Length

2022-09-05T21:40:15.442763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:15.565058image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
united5
25.0%
kingdom4
20.0%
ukraine2
 
10.0%
russian1
 
5.0%
federation1
 
5.0%
egypt1
 
5.0%
south1
 
5.0%
africa1
 
5.0%
brazil1
 
5.0%
netherlands1
 
5.0%
Other values (2)2
 
10.0%

Most occurring characters

ValueCountFrequency (%)
i15
 
10.7%
n15
 
10.7%
e12
 
8.6%
t11
 
7.9%
d11
 
7.9%
a10
 
7.1%
U7
 
5.0%
7
 
5.0%
r6
 
4.3%
o6
 
4.3%
Other values (21)40
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter113
80.7%
Uppercase Letter20
 
14.3%
Space Separator7
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i15
13.3%
n15
13.3%
e12
10.6%
t11
9.7%
d11
9.7%
a10
8.8%
r6
 
5.3%
o6
 
5.3%
g5
 
4.4%
m4
 
3.5%
Other values (10)18
15.9%
Uppercase Letter
ValueCountFrequency (%)
U7
35.0%
K4
20.0%
S2
 
10.0%
E1
 
5.0%
F1
 
5.0%
R1
 
5.0%
A1
 
5.0%
B1
 
5.0%
N1
 
5.0%
J1
 
5.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin133
95.0%
Common7
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i15
11.3%
n15
11.3%
e12
 
9.0%
t11
 
8.3%
d11
 
8.3%
a10
 
7.5%
U7
 
5.3%
r6
 
4.5%
o6
 
4.5%
g5
 
3.8%
Other values (20)35
26.3%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i15
 
10.7%
n15
 
10.7%
e12
 
8.6%
t11
 
7.9%
d11
 
7.9%
a10
 
7.1%
U7
 
5.0%
7
 
5.0%
r6
 
4.3%
o6
 
4.3%
Other values (21)40
28.6%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)69.2%
Missing75
Missing (%)85.2%
Memory size832.0 B
GB
UA
RU
EG
ZA
Other values (4)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters26
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)53.8%

Sample

1st rowRU
2nd rowEG
3rd rowZA
4th rowBR
5th rowUA

Common Values

ValueCountFrequency (%)
GB4
 
4.5%
UA2
 
2.3%
RU1
 
1.1%
EG1
 
1.1%
ZA1
 
1.1%
BR1
 
1.1%
NL1
 
1.1%
US1
 
1.1%
JP1
 
1.1%
(Missing)75
85.2%

Length

2022-09-05T21:40:15.662545image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:15.765440image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
gb4
30.8%
ua2
15.4%
ru1
 
7.7%
eg1
 
7.7%
za1
 
7.7%
br1
 
7.7%
nl1
 
7.7%
us1
 
7.7%
jp1
 
7.7%

Most occurring characters

ValueCountFrequency (%)
G5
19.2%
B5
19.2%
U4
15.4%
A3
11.5%
R2
 
7.7%
E1
 
3.8%
Z1
 
3.8%
N1
 
3.8%
L1
 
3.8%
S1
 
3.8%
Other values (2)2
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter26
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G5
19.2%
B5
19.2%
U4
15.4%
A3
11.5%
R2
 
7.7%
E1
 
3.8%
Z1
 
3.8%
N1
 
3.8%
L1
 
3.8%
S1
 
3.8%
Other values (2)2
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Latin26
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
G5
19.2%
B5
19.2%
U4
15.4%
A3
11.5%
R2
 
7.7%
E1
 
3.8%
Z1
 
3.8%
N1
 
3.8%
L1
 
3.8%
S1
 
3.8%
Other values (2)2
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G5
19.2%
B5
19.2%
U4
15.4%
A3
11.5%
R2
 
7.7%
E1
 
3.8%
Z1
 
3.8%
N1
 
3.8%
L1
 
3.8%
S1
 
3.8%
Other values (2)2
 
7.7%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)69.2%
Missing75
Missing (%)85.2%
Memory size832.0 B
Europe/London
Europe/Zaporozhye
Asia/Kamchatka
Africa/Cairo
Africa/Johannesburg
Other values (4)

Length

Max length19
Median length16
Mean length14.46153846
Min length10

Characters and Unicode

Total characters188
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)53.8%

Sample

1st rowAsia/Kamchatka
2nd rowAfrica/Cairo
3rd rowAfrica/Johannesburg
4th rowAmerica/Noronha
5th rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/London4
 
4.5%
Europe/Zaporozhye2
 
2.3%
Asia/Kamchatka1
 
1.1%
Africa/Cairo1
 
1.1%
Africa/Johannesburg1
 
1.1%
America/Noronha1
 
1.1%
Europe/Amsterdam1
 
1.1%
America/New_York1
 
1.1%
Asia/Tokyo1
 
1.1%
(Missing)75
85.2%

Length

2022-09-05T21:40:15.856558image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:15.956628image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/london4
30.8%
europe/zaporozhye2
15.4%
asia/kamchatka1
 
7.7%
africa/cairo1
 
7.7%
africa/johannesburg1
 
7.7%
america/noronha1
 
7.7%
europe/amsterdam1
 
7.7%
america/new_york1
 
7.7%
asia/tokyo1
 
7.7%

Most occurring characters

ValueCountFrequency (%)
o26
13.8%
r18
 
9.6%
a15
 
8.0%
e14
 
7.4%
/13
 
6.9%
n11
 
5.9%
p9
 
4.8%
u8
 
4.3%
E7
 
3.7%
A7
 
3.7%
Other values (23)60
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter147
78.2%
Uppercase Letter27
 
14.4%
Other Punctuation13
 
6.9%
Connector Punctuation1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o26
17.7%
r18
12.2%
a15
10.2%
e14
9.5%
n11
 
7.5%
p9
 
6.1%
u8
 
5.4%
i7
 
4.8%
c5
 
3.4%
d5
 
3.4%
Other values (11)29
19.7%
Uppercase Letter
ValueCountFrequency (%)
E7
25.9%
A7
25.9%
L4
14.8%
N2
 
7.4%
Z2
 
7.4%
Y1
 
3.7%
C1
 
3.7%
J1
 
3.7%
K1
 
3.7%
T1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/13
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin174
92.6%
Common14
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o26
14.9%
r18
 
10.3%
a15
 
8.6%
e14
 
8.0%
n11
 
6.3%
p9
 
5.2%
u8
 
4.6%
E7
 
4.0%
A7
 
4.0%
i7
 
4.0%
Other values (21)52
29.9%
Common
ValueCountFrequency (%)
/13
92.9%
_1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII188
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o26
13.8%
r18
 
9.6%
a15
 
8.0%
e14
 
7.4%
/13
 
6.9%
n11
 
5.9%
p9
 
4.8%
u8
 
4.3%
E7
 
3.7%
A7
 
3.7%
Other values (23)60
31.9%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing88
Missing (%)100.0%
Memory size832.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing86
Missing (%)97.7%
Memory size832.0 B
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUkraine
2nd rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine2
 
2.3%
(Missing)86
97.7%

Length

2022-09-05T21:40:16.057605image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:16.158362image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine2
100.0%

Most occurring characters

ValueCountFrequency (%)
U2
14.3%
k2
14.3%
r2
14.3%
a2
14.3%
i2
14.3%
n2
14.3%
e2
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter12
85.7%
Uppercase Letter2
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k2
16.7%
r2
16.7%
a2
16.7%
i2
16.7%
n2
16.7%
e2
16.7%
Uppercase Letter
ValueCountFrequency (%)
U2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U2
14.3%
k2
14.3%
r2
14.3%
a2
14.3%
i2
14.3%
n2
14.3%
e2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U2
14.3%
k2
14.3%
r2
14.3%
a2
14.3%
i2
14.3%
n2
14.3%
e2
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing86
Missing (%)97.7%
Memory size832.0 B
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUA
2nd rowUA

Common Values

ValueCountFrequency (%)
UA2
 
2.3%
(Missing)86
97.7%

Length

2022-09-05T21:40:16.252807image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:16.348035image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ua2
100.0%

Most occurring characters

ValueCountFrequency (%)
U2
50.0%
A2
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U2
50.0%
A2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U2
50.0%
A2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U2
50.0%
A2
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing86
Missing (%)97.7%
Memory size832.0 B
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters34
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEurope/Zaporozhye
2nd rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye2
 
2.3%
(Missing)86
97.7%

Length

2022-09-05T21:40:16.431493image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:40:16.513792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye2
100.0%

Most occurring characters

ValueCountFrequency (%)
o6
17.6%
r4
11.8%
p4
11.8%
e4
11.8%
E2
 
5.9%
u2
 
5.9%
/2
 
5.9%
Z2
 
5.9%
a2
 
5.9%
z2
 
5.9%
Other values (2)4
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter28
82.4%
Uppercase Letter4
 
11.8%
Other Punctuation2
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o6
21.4%
r4
14.3%
p4
14.3%
e4
14.3%
u2
 
7.1%
a2
 
7.1%
z2
 
7.1%
h2
 
7.1%
y2
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E2
50.0%
Z2
50.0%
Other Punctuation
ValueCountFrequency (%)
/2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin32
94.1%
Common2
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o6
18.8%
r4
12.5%
p4
12.5%
e4
12.5%
E2
 
6.2%
u2
 
6.2%
Z2
 
6.2%
a2
 
6.2%
z2
 
6.2%
h2
 
6.2%
Common
ValueCountFrequency (%)
/2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o6
17.6%
r4
11.8%
p4
11.8%
e4
11.8%
E2
 
5.9%
u2
 
5.9%
/2
 
5.9%
Z2
 
5.9%
a2
 
5.9%
z2
 
5.9%
Other values (2)4
11.8%

Interactions

2022-09-05T21:40:05.767526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.260387image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.230449image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.167897image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.003047image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.871669image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.749196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.573580image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.435549image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.241403image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.073373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.932786image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.842775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.456531image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.300543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.244092image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.071908image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.940302image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.817799image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.643746image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.502466image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.311701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.137521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.003370image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.916739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.538880image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.380215image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.317803image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.155920image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.017652image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.894453image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.718694image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.582506image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.387788image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.212030image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.075551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.988608image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.610811image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.454126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.384003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.230608image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.094935image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.971523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.791685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.652020image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:39:56.687099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:40:01.945218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.793062image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.607097image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.424299image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.281840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:06.196581image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.824837image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.696829image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.588484image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.453983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.319249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.181581image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.018003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.856400image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.673678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.496536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.351612image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:06.268134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.889002image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.780438image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.659587image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.522926image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.391616image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.247869image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.085852image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.919376image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.745267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.565879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.418043image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:06.327768image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:56.954840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:57.853294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:58.722102image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:59.590976image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:00.458359image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:01.309281image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.152563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:02.979632image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:03.807886image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:04.630036image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:40:05.480028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:40:04.003860image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:40:05.694624image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:40:16.605749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:40:16.849704image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:40:17.096207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:40:17.382028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:40:06.891495image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:40:07.610980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:40:08.203567image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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02179612https://www.tvmaze.com/episodes/2179612/kontakty-1x29-kontakty-v-telefone-nikolaa-soboleva-klava-koka-eldar-dzarahov-andrej-malahov-edvard-bilКОНТАКТЫ в телефоне Николая Соболева: Клава Кока, Эльдар Джарахов, Андрей Малахов, Эдвард Бил129.0regular2020-12-0912:002020-12-09T00:00:00+00:0046.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901422.jpghttps://static.tvmaze.com/uploads/images/original_untouched/360/901422.jpghttps://api.tvmaze.com/episodes/217961249630https://www.tvmaze.com/shows/49630/kontaktyКонтактыGame ShowRussian[]Running30.042.02019-04-03Nonehttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI[Monday]NaN22NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpgNone1661485729https://api.tvmaze.com/shows/49630https://api.tvmaze.com/episodes/2380515NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11986871https://www.tvmaze.com/episodes/1986871/kotiki-1x08-seria-8Серия 818.0regular2020-12-092020-12-09T00:00:00+00:0013.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198687152198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN15NaN510.0Epic MediaNaNNoneNaNNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpgNone1637555191https://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21983257https://www.tvmaze.com/episodes/1983257/mertvye-dusi-1x01-seria-1Серия 111.0regular2020-12-092020-12-09T00:00:00+00:0043.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719751.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719751.jpghttps://api.tvmaze.com/episodes/198325752316https://www.tvmaze.com/shows/52316/mertvye-dusiМёртвые душиScriptedRussian[Comedy]Ended43.043.02020-12-092020-12-16https://www.ivi.ru/watch/mertvyie-dushi-2020[Wednesday]NaN21NaN337.0iviNaNhttps://www.ivi.ru/NaNNaN393060.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>1608253013https://api.tvmaze.com/shows/52316https://api.tvmaze.com/episodes/1983260NaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31983258https://www.tvmaze.com/episodes/1983258/mertvye-dusi-1x02-seria-2Серия 212.0regular2020-12-092020-12-09T00:00:00+00:0043.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719752.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719752.jpghttps://api.tvmaze.com/episodes/198325852316https://www.tvmaze.com/shows/52316/mertvye-dusiМёртвые душиScriptedRussian[Comedy]Ended43.043.02020-12-092020-12-16https://www.ivi.ru/watch/mertvyie-dushi-2020[Wednesday]NaN21NaN337.0iviNaNhttps://www.ivi.ru/NaNNaN393060.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/719749.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719749.jpg<p>A modern adaptation of the classic novel-poem by Nikolai Gogol. The action takes place in our days. Chichikov, an enterprising and not without charm official from Moscow, this time does not buy up dead souls from small-minded provincials, but sells them places in the cemetery next to celebrities. He arrives in the County town of N and quickly makes" big and small " connections there. These bright acquaintances will benefit him and open up new opportunities for personal gain.</p>1608253013https://api.tvmaze.com/shows/52316https://api.tvmaze.com/episodes/1983260NaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41971569https://www.tvmaze.com/episodes/1971569/mermaid-prince-2x09-episode-9Episode 929.0regular2020-12-0911:002020-12-09T02:00:00+00:0015.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197156947207https://www.tvmaze.com/shows/47207/mermaid-princeMermaid PrinceScriptedKorean[Drama, Romance, Mystery]Ended15.015.02020-04-142020-12-10None11:00[Wednesday, Thursday]NaN34NaN380.0SeeznNaNhttps://www.seezntv.com/NaNNaN380686.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/283/709704.jpghttps://static.tvmaze.com/uploads/images/original_untouched/283/709704.jpg<p><b>Mermaid Prince</b> is about Hye Ri, who embarks on a graduation trip to Gangwon Province and meets Woo Hyuk, a mysterious guy who runs a guest house.</p>1610205155https://api.tvmaze.com/shows/47207https://api.tvmaze.com/episodes/1971570NaNKorea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
51985044https://www.tvmaze.com/episodes/1985044/wan-sheng-jie-2x11-enough-money-was-left-for-this-episodeEnough money was left for this episode211.0regular2020-12-0910:002020-12-09T02:00:00+00:004.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198504448395https://www.tvmaze.com/shows/48395/wan-sheng-jieWan Sheng JieAnimationChinese[Comedy, Anime, Supernatural]Running4.04.02020-04-01Nonehttps://v.qq.com/detail/a/awnia0n2erqryf3.html10:00[Wednesday]NaN16NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN380207.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/259/648137.jpghttps://static.tvmaze.com/uploads/images/original_untouched/259/648137.jpg<p>The pure and cute little devil Nini lives in Room 1031 of Wan Sheng Street Apartment. His roommates are no ordinary people: The lazy and wacky vampire Ira who spends most of his time gaming or watching TV, the unlucky dancer werewolf Vladimir, the serious and old-fashioned angel landlord Lynn and his naive little sister Lily, and many more.<br /><br />What none of them realize is that the power of the demon king is sleeping inside of Nini. With evil forces in hot pursuit, can Nini and his friends head off disaster?</p>1647193542https://api.tvmaze.com/shows/48395https://api.tvmaze.com/episodes/2280228NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
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